Personal Statement Essay Example for Free

Personal Statement Essay In rerouting my life for a better future, I have chosen to pursue computer science. Upon setting foot in Houston Community College (HCC), I enrolled in engineering chemistry. However, I have decided to seriously take computer science in the prestigious school of University of California (UC). My desire to switch course and school has been influenced by the fact that I find less satisfaction with the present course I am taking. Until, I realized that computer science is my professional call and UC will be the best school that will fully educate me and will develop my skills and capabilities to its maximum potential. My intention and interest to take computer science is brought by the fact that today’s era is marked by computer and technology. The technological innovation is unstoppable and drastic. Through which, the demand for computer scientists has also intensified. In addition, my interest in computer science is molded by my innate interest in math and chemistry. Even as a kid, I had been excelling in math. I believe that my talent in loving and easily grasping the complexities of math is a God’s given ability that will eventually lead me to the life I had always wanted. As such, I want to blend my talent with the demand in the society in the field of computer science. Furthermore, I have considered that having a career in technologically- innovated field would effectively make me a better person and a contributor to the society. As an ordinary person, I also wished to be of help to other people, especially to the needy. In this era, I have seen many who are still striving to adopt the culture and to learn computer. For some students and other unemployed, they find their innocence and ignorance to technology as an adversity that hinders them to change their life for the better. Among the unemployed, they have admitted having been denied work due to their inadequate knowledge in computers. As a good citizen, I want to help in minimizing this common problem in the society. This could also be my chance to help in giving hope to those who are discouraged because of their ignorance in technology. For this reason, I have made a firm decision to pursue computer science. Interestingly, the church has been one of the major influences in my life and to my decisions. In church, helping other people is always reiterated. Even to an ordinary person, it is natural to extend help to others. At church, I had been an active member of the band as a singer and sometimes playing the drums. During services, our band leads the song. Through my membership in church activities, my self-esteem and socialization skills have been improved. Significantly, leading the whole church to sing and maintaining the momentum of praise is not an easy task. Taking the lead in singing is important in order to give the expectation of the church-goers and try to persuade them to sing in chorus. Aside from that, it is also important that the message of the song is being delivered well and understood by the attendees. In doing so, it is necessary that the songs that are being played correspond to the mood of the people. In addition to my membership in a band, the church to where I am affiliated also exposed us to charity works and volunteering activities. Some of the activities include mentoring children about values and religious teachings. We also initiated programs for the underprivileged by going to their places and provide foods and clothing. My experiences and membership in a group greatly improved my perception about friendship and trust. Significantly, my involvement in community services has nurtured my idea on grace and benevolence. As a band member, I had the chance of meeting real friends I can truly trust for every simple secret shared. In doing community service, I felt the satisfaction that any material things can ever offer to me. Having seen a smile among the children happy in receiving our aids brought joy to my heart. From there, I committed myself to maximize my capability in helping other people. I also realized that it is through extending financial and emotional help and eventually changing other’s life for the better is a way by which I can truly say to myself that I am an asset of the society. For these noble reasons, I decided to pursue computer science. As a human being, mere experiences and perception of the future is not enough motivation or factor in achieving goals. Values and characters are also important for it helps one in making his decisions and on how he looks at things. In life, there are plenty of struggles that everyone has to meet. These struggles may comprise of problems and temptations. As for me, I have plenty of struggles that have kept on pulling me down from fulfilling my dreams. The diversity factor is one thing that usually weakens my self-esteem. Aside from that, I am also living away from my family which makes me feel alone most often. However, I have to overcome these adversities in order to achieve my dreams. In having this kind of thinking, being optimistic has helped me a lot. Since childhood, I always viewed things in the positive light. I try not to be discouraged by any disappointments that may come in my life. My battles with diversity have been won through optimism and courage. Furthermore, in surviving the trials in life and in ensuring success in the future, I believe that it is vital to be honest, persistent, and determined in everything that I have to do. Before coming here in United States and since childhood, my parents have reiterated the importance of these values in life. As I grew old, I realized that my parents are right. At this stage of my life, I need to be persistent and determined so that I will be able to fulfill my purpose in life.

Deregulation Of Downstream Oil And Gas

Deregulation Of Downstream Oil And Gas It is largely assumed by Nigerians that the government involvement in the management and ownership structure of the refineries and logistics infrastructures is the cause of the numerous problems associated with the downstream oil and gas industry. Thus, the government economic reforms by way of deregulation policy was established in 2003 to revive the ailing industry. This dissertation seeks to examine the deregulation of the downstream oil and gas industry in Nigeria, a strategic management perspective of the effects, challenges and prospects. The objective of this study is to have both theoretical and practical knowledge contribution on deregulation. This study theoretical framework is embedded in three literatures: deregulation, strategic management and competitive forces. These three perspective are used in order to assess the emerging effects, challenges and prospects that the industry has on the changing strategic landscape of the deregulation exercise. The literature for this perspective, competitive forces and innovation management were reviewed: The reason for this perspective is that the competitive forces provides the understanding of the industry structure and the interactions between competitors, while innovative management is to understand the industry processes and capabilities. By summarizing and integrating these viewpoints formed a hypothesized understanding that reflected the effects, challenges and prospects of deregulation. In order to obtain an empirical analysis of the study a social constructed research methodology that is based on quantitative and qualitative method were argued for. A non-probability sample approach with a dichotomous questionnaire of (YES/NO) was self-administered in three states Abuja, Lagos and Port Harcourt to represent the three geographical areas in Nigeria, the target population of fifty persons from each state was chosen using purposive sampling method. Furthermore, an open-ended questionnaire were self-administered on two managers from Forth Oil, One Manager from Oando Plc and One Manger from Total Plc. The managers views were sort in order have industry professionals opinion on the deregulation of the downstream oil and gas industry. The data collected were analysed with the use of SPSS to determine the effects, challenges and prospects of the deregulation of the downstream industry. A Porters five model was also utilised to analyse the competitiveness in the industry. The result of the analysis shows how firms within the downstream oil and gas industry have changed and responded towards deregulation. It further shows how the previous regulated regime of the downstream oil and gas industry has been transformed to become more competitive and market driven. The analysed result shows a slim margin between the (yes/no) responses on the effects and challenges of deregulation, while there was a significant margin on the response in favour of the prospects and opportunities of downstream oil and gas deregulation. Overall, the result shows that many Nigerians are in support that deregulation will deliver positive effects, reduce the challenges in in the industry and also create better prospects and opportunities. The study findings indicates that the downstream oil and gas industry is not fully deregulated to enable market forces of demand and supply to determine product price, rather government have been fixing petroleum product prices. Most of the industry challenges are still persistent, like fuel scarcity, corruption, smuggling, and ineffective refinery. Thus, the expected benefit as promised by the government is yet to be achieved. However, based on the overall response of the respondent, this study can infer that many Nigerians support the government deregulation of the downstream oil and gas industry. CHAPTER ONE 1 INTRODUCTION 1.1 BACKGROUND The advent of deregulation reform dates back to 1973 after the first oil shock experience, which led to a decline in the economic growth of most developed economies Nordhaus, Houthakker and Sachs (1980); Sachs (1982) and labour productivity growth Baily, Gordon, Solow (1981). Further to the mid-1970s productivity decline, a wide range of policy responses, including economic deregulation were introduced. The inception of deregulation reform was initiated in the US Winston (1998); Morgan (2004), while the UK and other developed economies followed in the early 1980s Pera, (1988); Healey (1990); Matthews, Minford, Nickell and Helpman (1987). The reform was also copied by the new democracies and many developing countries in the 1990s leading to wide range of labour, capital and product market reforms. This was the scenario that prevailed throughout the early 21st century Wolfl, Wanner, Kozluk and Nicoletti (2009) until the global economic and financial crisis determined the credibility o f relaxing economic growth. Like many other developing countries that copied the market reform, Nigeria being a growing economy with an increase in demand for commodities such as petroleum products Nwokeji (2007) meeting the supply needs remains a big challenge due to frequent breakdown of the refineries and over-reliance on importation. Although prior to 1960s the downstream oil and gas sector was initially market driven with the mechanism of demand and supply determining product price Funsho (2004). The distribution and marketing of petroleum product was virtually controlled by the multinational oil and gas companies Jean (2012). This was the situation before the government decided to harmonise petroleum products by way of uniform pricing in 1973 to encourage even distribution of products nationwide Christopher and Adepoju (2012). In furtherance to the uniform price policy and also tackle the cost differential problem associated with the delivery of products to every part of the country, the government establ ished the Petroleum Equalization Fund (PEF) Oluwole (2004). The participation of government in the management and ownership structure of the downstream sector culminated to a regulated regime Olumide (2011). The consequence of the policy shift by the government on the economy was characterized by acute product scarcity, hoarding, smuggling, adulteration; long queues, inappropriate pricing, under funding and monopolistic practices. This were the main features of the supply and distribution process of the downstream oil and gas industry Funsho (2004). The unhealthy development degenerated to poor performance of the nation refineries, which resulted in excessive dependence on imports Christopher and Adepoju (2012). Thus, the economic reforms of the government became imperative towards reviving the ailing downstream sector by way of deregulation Okafor(2004). The deregulation of the sector as implemented in 2003 implies removal of restrictions on the establishment of refineries, jetties and depots. It also involves granting free access to private sector participation in the importation of petroleum products and also allowing the demand and supply mechanism to determine price including also the government total removal of control on product prices Oluwole (2004). Furthermore, the objective is meant to achieve regular supply of petroleum products at reasonable price, maintaining self-sufficiency in refining, employment generation for Nigerians, growth in foreign investment and general economic growth. Onyishi, Emeh, and Ikechukwu (2012). Other major benefits are as indicated in figure 1 below: Figure : BENEFITS OF DEREGULATION OF DOWNSTREAM OIL AND GAS SECTOR Removal of subsidy burden Government refocus to segment regulator Competition on and a level play field to attract new entrant DEREGULATION Increased efficiency by service providers Eliminate sharp practices that exploit subsidy regime From the foregoing many years have passed after deregulation, yet the aforementioned problems still persist, refineries continue to operate below installed capacity Oladele (1997). Efficient transport system for product distribution is lacking while pipeline are still vandalized. The expected government responses by private sector investment in establishing new refineries after many years of issuance of licence is yet to be realized. This scenario is in contrast to the objective of deregulation as commenced in the USA in the 1970s which was to create competition, enhance industry efficiency and guarantee competitive prices DME (2007) ; Hicks (2004). Improving efficiency in the industry implies product availability, proper functioning of the distribution networks, availability of storage facilities and depots to avoid scarcity of products and to ensure regular supply of products to force down price. However with the lack of these facilities the intending benefit from deregulation of the downstream oil and gas sector by the Nigerian populace becomes defeated. The question now is why should government proceed with deregulation policy? Thus, this dissertation seeks to examine a strategic management perspective of the effects, challenges and prospects of the deregulation of the downstream oil and gas industry in Nigeria. The theoretical framework of this study dwells on three literature reviews: deregulation, strategic management and competitive forces. This three perspectives are utilized to assess the emerging effects, challenges and prospects of the deregulation exercise in the oil and gas industry. The study analyses the literatu re for this perspectives, competitive forces and innovation management in the context of deregulation. 1.2 PURPOSE OF THE STUDY The purpose of this study is to appraise the deregulation exercise that was carried out in the Nigerian downstream oil and gas industry. The specific aim of this study are as follows: To examine the implementation of deregulation policy in the downstream oil and gas industry in order to determine the effects, challenges and prospects. This study is also aimed to explore if deregulation has actually yielded the desired result in terms of the forces of demand and supply determining prices of product. This study further uses the Porters five model to establish if effective strategic management (innovative management and competitive forces) can achieve a sustained competitive advantage among industry competitors in the deregulated regime. 1.2 RELEVANCE OF THE STUDY This study is relevant in many ways; apart from the downstream sector importance in Nigeria economic stability other relevance includes the following: As already stated, this study would use a Porters five competitive forces to analyse the attractiveness of the industry. This will inform us of the impact of deregulation on new entrants, competitive rivalry, buyers bargaining powers, suppliers power, products prices, product supply and distribution. The study would conduct a survey to know the feelings of Nigerians on the effects, challenges and prospects of the deregulation of the downstream industry. The study would also contribute to existing literature on deregulation thereby providing insight of current developments in the downstream oil and gas industry in Nigeria. Furthermore, the study would also serve as an important tool for students, academia, institutions and individuals to consult for knowledge on deregulation of the downstream sector of the Nigerian oil and gas industry. 1.3 RESEARCH QUESTIONS In finding out the effects, challenges and prospects of the deregulation of downstream oil and gas industry in Nigeria, this study answers three questions: How can government improve the implementation of the deregulation of the downstream oil and gas industry to achieve the actual policy objective? In what way can government encourage the private sector to fully participate in the downstream oil and gas deregulation exercise? What informed the government deregulation of the downstream oil and gas industry and if it is the only solution in an economic environment such as Nigeria? 1.4 ORGANISATION OF THE STUDY This study contains six chapters. The first chapter is the introduction and background of the study, the purpose of the research, significance of the study, the objectives of the study, the research questions, this would guide the study. Chapter two would present the literature review on the subject matter. Chapter three gives the theoretical framework of the study. The methodology to be adopted in the study would be stated in chapter four. Chapter five focuses on the presentation of data, analysis of collected data, findings and discussion of results. The last chapter which is chapter six, would present the conclusion and appropriate recommendations. CHAPTER TWO 2.0 LITERATURE REVIEW Many existing literature have argued on different perspectives and motives for the government deregulation of the oil and gas sector in Nigeria yielding different opinions from two school of thought. The opposing and the supporting group respectively. Those supporting deregulation argue that deregulation of the downstream oil and gas industry would actualize government move to eradicate fuel scarcity and ensure constant fuel supply across the country Funsho (2004). Similarly, deregulation of the industry would create inflow of foreign investment while persistent smuggling of petroleum products and inefficiencies in the sector will be eliminated Oluwole (2004). They also posit that Nigeria has the lowest price of petroleum products in the world and with deregulation the international market equilibrium would allow government to channel funds to other sectors of the economy. Furthermore, they argued that it would break the monopoly enjoyed by the Nigerian National Petroleum Corporation (NNPC) Okafor (2004). Essentially, deregulation would lead to uninterrupted operation of the refineries, it would also guarantee steady supply by enabling stakeholders and independent marketers to participate in product importation and marketing Enemoh (2004). Their view is also that the regulated regime by way of subsidy is a way of government enriching few Nigerian petroleum products marketers Oluwole (2004). Findings from Abu (2012) indicates that Nigerians believes deregulation and privatization will usher in sustainable development and would be a blessing rather than a course. Odey (2011) recommends the complete deregulation of the downstream sector to reduce corruption, inaccurate record keeping, inefficiency, smuggling and insufficient product supply. Jean (2012) suggested that making deregulation work involves providing an enabling environment and framework for efficient production, supply and distribution. Braide (2003) recommends that the usual business as usual in the NNPC by way of product imp ortation and distribution is inexpedient because it represents a wrong step for government to continue with instead government should fully deregulate the downstream oil and gas sector. From the opposing group came the argument that the Nigeria petroleum industry must not be deregulated completely, instead government should maintain the status quo and restructure the sector to improve efficiency for the overall national interest. They opined that the root cause and clamour for deregulation is because of the massive corruption in the sector and therefore should be tackled rather than embarking on deregulation. They further argued that deregulation helps increase profit margin for the importers, interestingly this is the position of the labour union and the organized civil society. Furthermore, Amana and Amana (2011) asserts that the fair distribution of economic benefits derived from petroleum has proven elusive and therefore predicts same for deregulation. Ibanga (2011) argued that removal of subsidy may cause dislocation to the gas price because of high demand and inadequate supply. Bafor (2001) doubted government sustaining the gain of deregulation due to the undu e interference in NNPC affair resulting to near collapse and dismal performance which encouraged the clamour for the privatisation and deregulation. According to Kikeri and Nellis (2004) they argued that deregulation processes and institutions must be combined with appropriate competition policies and regulatory frameworks without which the gains of deregulation can be eroded by harsh impact on consumers and the overall economy affected due to inadequate product supply. Matthew and Fidelis (2003) opined that the merit of deregulation can only be enjoyed by Nigerians if only they could be genuine attention to eliminating corruption in the sector. Adagba, Ugwu and Eme (2012) posits that government is merely taxing the poor to subsidise the life of the rich. Similarly, Akpanuko and Ayandele (2012) argues that government is not transparent in its drive to transform the economy and suggested reduction in the cost of governance, rehabilitating the refineries as a measure to drive the economy. In global perspective, the theoretical argument behind the large scale deregulation reforms initiated in the late 1970s is two-fold. On one hand, deregulation reduces the rents that regulation creates for workers, incumbent producers, and service providers. This view has gained a widespread popularity among academics and policy makers ever since the works by Stigler (1971); Posner (1975) and Peltzman (1976) contributed to the understanding of the political economy of regulation. On the other hand, deregulation allows the newly created competition on product, labour and capital markets to determine the winner of rent transfers. Thus, by spurring productivity and efficiency gains Winston, (1993), economic deregulation ultimately contributes to the overall increase in economic growth. The additional growth is brought primarily through increased employment and real wages Blanchard Giavazzi (2003), which impacts both production and consumption and through increased investment Alesina, Ardagna, Nicoletti, Schiantarelli (2005), this affects the capital stock in the economy. However, a need for caution is required on the recent take on the efficiency gains from deregulation in the developing world. The key argument in this new area of literature is that deregulation reforms influence diverse economies differently, depending on their position on the technology level and on their quality of institutions. For example, Acemoglu, Aghion and Zilibotti (2006) claim that certain restrictions on competition may benefit the technologically backward countries, while Estache and Wren-Lewis (2009) finds that ideal regulatory policies in developed and in developing countries are different because of differences in the overall institutional quality in those countries. In addition, Aghion, Alesina and Trebbi (2007) use industry level data to demonstrate that within each economy, institutional reforms influence different industries differently, and more specifically, industries closer to the technology frontier would be affected more by deregulation and would innovate more than the backward industries in order to prevent entry. As a result, countries closer to the technology frontier would benefit more from deregulation. The alleged benefits of economic deregulation in many industries prompted a debate on the growth effects from specific types of reforms on petroleum product downstream deregulation. 2.1 THEORIES OF DEREGULATION Deregulation can be looked from the angle of different theories, we have the public interest theory which presume that deregulation would occur if the market deficiency which compelled regulation in the first place were to disappear. An illustration is a change in technology which could eliminate a natural monopoly. The public interest theory also predicts that deregulation would occur if discovered that a regulatory regime which had been perceived to be in the public interest was defective. It may turn out that, in the light of experience, the cost of the regulatory apparatus is or has become greater than the loss resulting from the market imperfection it was designed to correct Posner (1974). Thus, it may become obvious only with experience that entry restrictions is a relatively costly way to enforce standards. From Stigler Peltzman came the version of the special interest theory which suggests that a number of factors which may give rise to deregulation. First, a reduction in the cost consumers must incur in order to inform themselves regarding the effect of regulation on them. For example, price comparisons between regulated and non-regulated controls can assist consumers in estimating the effect of regulation on the prices they pay. Secondly, as product substitutes increases between regulated and non-regulated products, this would reduce profits and hence the urge to lobby for regulation induced price increases. Substitution may also occur between regulated and unregulated industries or between regulated and unregulated controls. Thirdly, a change in industry structure can reduce either the incentive or the ability to lobby for regulation. Also, an increase in the number of firms in an industry or a merging of their respective interests may increase the incentive to free ride and make it more costly to organize support for politicians promising regulatory benefits Stigler (1974). Noll and Owen (1983) argue that, over time, the beneficiaries of regulation will grow while groups that lose will contract. In view of the interest group structure, alternative for substitutes and information, McCormick et al. (1984) offer two reasons why the incentive to regulate is greater than the incentive to deregulate. The first is that the cost of seeking regulation may be as much as the present value of the anticipated wealth transfer involved, and if this cost is sunk it is not recoverable in the event of deregulation. The question is does Nigeria have a theory of deregulation? although the public and special interest theories of deregulation had slightly been criticized for the vagueness regarding transactions in policy frameworks and political markets. In the case of Nigeria the evidence on deregulation supports both the public and special interest theories. The two of them are in the same range, deregulation is used by government to effect wealth transfers through privatization. These transfers may benefit the highly concentrated special interest groups, such as petroleum product marketers and politicians. They may also benefit larger groups, like the deregulation of telecom industry. For the public interest group, government most times come up with reforms and policy frame work aimed at benefiting the masses, but often hijacked by the cabals who may want to exploit government programme to their own benefit. An example is the issue of oil subsidy which the original government intention was for p ublic interest, but was later hijacked by special interest groups or cabals. 2.2 COUNTRY EXPERIENCES ON DEREGULATION 2.2.1 ARGENTINA The Menem administration introduced deregulation in Argentina. The country underwent heavy economic deregulation, privatization and had a fixed exchange rate between (1989-1999). The resulting effects of Argentina deregulation exercise lead to the comparing of Enron with Argentina by Krugman (2001), asserting that they were both experiencing economic collapse due to excessive deregulation. However the claim by Krugman was termed as confusing correlation with causation, as neither the collapse was due to excessive deregulation Herbert (2002). He argued that if deregulation of the Argentine economy produced prosperity for years, how could it generate collapse within a few months? The answer is not deregulation but excessive loans. 2.2.2 AUSTRALIA Deregulation in Australia commenced with the Minimum Effective Regulation in 1986 following the announcement by the Labour Prime Minister Bob Hawke of a wide range of deregulatory policies. The introduction of the policy, which is now a familiar requirements for regulatory impact statements, took many years for governmental agencies to comply with. Although wider competition policy reforms had commenced, during the 1980s trade policy reform which substantially increased competition in the domestic economy Smith (2001). In this regard the level of assistance to manufacturing sector was reduced from 25 percent to 15 percent of the value of manufacturing output between 1981-82 and 1991-92. They was reductions in import barriers, which off course exposed many industries to the rigours of international competition, providing increased incentives to improve product quality, costs and innovation. 2.2.3 CANADA The deregulation of natural gas in Canada took place in the mid 1980s, with exception of Atlantic provinces, Vancouver Island and Medicine Hat, the whole of the country natural gas was deregulated. A price comparison service is operating in some of these jurisdictions, particularly Ontario, Alberta and BC. The other provinces are small markets and have not attracted suppliers. Customers have the choice of purchasing from a local distribution company (LDC) or a deregulated supplier. In most provinces the LDC is not allowed to offer a term contract, just a variable price based on the spot market. LDC prices are changed either monthly or quarterly. 2.2.4 UNITED KINGDOM The conservative government of Margaret Thatcher started a program of deregulation and privatization in 1979, where the conservative government criticised many public enterprises, including CEGB, for being too inflexible, bureaucratic and out of political control. As a remedy the government suggested deregulation and privatisation Foster (1993) ; Newbery and Green (1996). In response, the policy framework was enacted which included the express coach Transport Act 1980, British Telecom 1984, privatization of London Bus services 1984, local bus services Transport Acts 1985 and the railways 1993. The common feature of all the privatisations was the offering of the shares to the general public. In support of the policy since 1997 the Labour governments of Tony Blair and Gordon Brown developed a programme of better deregulation. This included a general programme for government departments to review, simplify or abolish their existing regulations, and introduced approach to new regulations . 2.2.5 NEW ZEALAND The New Zealand governments adopted policies of extensive deregulation from 1984 to 1995. Originally initiated by the Fourth Labour Government of New Zealand Dalziel (2010). The goal of the policy was liberalising the economy and had a comprehensive coverage and innovations. The major specific polices included: establishing an independent reserve bank; floating the exchange rate; public sector finance reform based on accrual accounting; performance contracts for senior civil servants; tax neutrality; subsidy-free agriculture; and industry neutral competition regulation. The introduction led to Economic growth in 1991. New Zealand was changed from a somewhat closed and centrally controlled economy to one of the most open economies in the OECD Evans, Grimes, Wilkinson (1996). 2.2.6 UNITED STATES Many industries in the United States became regulated by the federal government in the late 19th and early 20th century. Entry to some markets was restricted to stimulate and protect the initial investment of private companies into infrastructure to provide public services, such as water, electric and communications utilities. However in the 1970s among the problems that encouraged deregulation was the way in which the regulated industries often controlled the government regulatory agencies, using them to serve the industries interests. In the energy industry the Emergency Petroleum Act was a regulating law, consisting of a mix of regulations and deregulation, which passed in response to OPEC price hikes and domestic price controls which effected the 1973 oil crisis in the United States. After adoption of this federal legislation, numerous state legislation known as Natural Gas Choice programs have sprung up in several states which allow residential and small volume natural gas users to comparison purchase from natural gas suppliers, aside with traditional utility companies. 2.3 CONCEPT OF DEREGULATION Deregulation refers to a situation whereby they is a restrictive use of the states legal power to direct the conduct of private actors Stigler (1971). Deregulation programme is focused primarily on the withdrawal of economic interest of government apparatus. It is also the reduction of government regulation of business, consumers and market activity Economic glossary (2013). Similarly deregulation according to Webster dictionary is the act or process of removing state deregulations, it is the opposite of regulation which implies the process of government regulating certain activities. In the perspective of Kimberly (2013) deregulation is when the government seeks to allow more competition in an industry that allows near-monopolies. From the view of Ernest and Young (1988) deregulation and privatization are elements of economic reform programmes charge with the goal of improving the overall economy in a structured process. Essentially in an economic perspective deregulation implies freedom from government control Innocent and Charles (2011), while Akinwumi et al (2005) asserts that deregulation is the removal of government interference in running a system. By implication, the normal regulatory rules and enforcement in managing the operation of a system is replaced with market force of demand and supply to be a determinant of price Ajayi and Ekundayo (2008). In the opinion of Wolak (2005) he sees deregulation as the removal of control by government on natural monopolies in order to exercise market power. Where for example in US regulation generally held natural monopolies to a specified rate of return basis for pricing products Rothwell and Gomez (2003). Deregulation introduced free market principles and competition into these natural monopolies Hirsch (1999); Kahn (2004); Novarro and Shames (2003); Rassenti, Smith and Wilson (2002) and created the frame breaking changes. The deregulation of downstream oil and gas industry is the loosening of government control over the industry. It is a way of breaking the monopoly in NNPC in order to pave way for healthy competition. This implies the introduction of free market system, where the forces of demand and supply are allowed to determine the market price of products PPPRA (2004). This formula is in contrast to the regulated regime, where government acting on existing laws controls and determine retail and wholesale prices of petroleum products. A regulated regime is characterised by low level of competition and investment leading to distortions in product supply and distribution, scarcity resulting to long queues, hording, smuggling and other bottlenecks such as monopolistic practices, existence of subsidy and poor maintenance of infrastructural facilities Funsho (2004). The structural framework of deregulation involves the following phases: (1) Liberalisation (2) Privatization and commercialization. 2.3.1 LIBERALIZATION Liberalization refers to a relaxation of the government previous restrictions, usually in areas of social or economic policy, in most context the process or concept is often, but not always referred to as deregulation Sullivan, Arthur, Sheffrin and Steven (2002). It is also the involvement of many participants in the downstream petroleum industry PPPRA (2004). Liberalization involves removing monopoly, promoting high competitive culture in the industry, product availability, ensuring fair pricing for consumer, reviving and ensuring the efficiency of the refineries Oluwole (2004). Liberalization also ensures the removal of oil subsidy, which robs the poor to pay the rich PPPRA (2004). Liberalization is aimed to generate add

Theres a Stranger in my Words :: Creative Writing Essays

There's a Stranger in my Words As I sit here and stare at the Mac I wonder who sits at my back? If they knew what I write Would they curse me and bite Or start up some verbal attack? Well, as I walk through the swirling, smoke filled sky of the Hagg-Sauer doorway, squeezing my eyes shut against the reflected sunlight, I thought about how I would approach this project. How to say what I need to say, without saying it in a way that has been said a thousand times, in a million-million words. The voices in my head struggle to escape to the paper, but there's this thing in between my thoughts and your eyes...my mind. Language that I would _never_ actually use in speaking to someone seems to just flow, driven by some primal "college survival" instinct, from my fingertips when I sit down at the word-hatcher with an assignment in hand. This has become a real dilemma, as I now struggle for true expression and attempt to beat back the demons of 15 years worth of practice at the 'official style' of writing. _I feel that I have become quite well adapted to writing the language which has become the "common coin of the realm" at colleges and Universities._ I could sit here and write puffed up, stagnant, and wordy paragraph after paragraph, and still hold the interest of many of my instructors. But that is not my desire...I seek to free my muse from the shackles of formulae, the bondage of format, and the unrelenting ambiguity of "the same old stuff." When does your _voice_, that engaging part of your writing which bridges topic and audience, become sensible and engaging? Is it when you _feel it_ working, when the point seems to be making its way onto the page or screen in front of you? Does it depend more on the person reading the thing you gave them? If this is true, then our discussion begins to degenerate into the absurd... If the success of my writing comes from you, the reader, then I can never be sure of its effectiveness before talking to you about it, can I? And if this is the case, then maybe it is best that there _is_ a fixed format to write into with college work. Pigeon holes, indeed! And yet, when the smoke clears and the debris is swept away, sometimes I feel that the real me, my thoughts and feelings, come through onto the page.

I Never Sang for my Father Essays -- essays papers

I Never Sang for my Father The father son relationship is very important. A growing boy needs a strong fatherly presence in order to become a â€Å"man†. The plays, â€Å"I Never Sang for my Father,† and â€Å"The Owl Killer,† and the short story â€Å"Notes to a Native Son,† show this. The lack of communication and basic affection from their fathers directly affected the sons’ mental health, including self-esteem. The father in â€Å"I Never Sang For My Father,† Tom, was very mentally and physically abusive. Many times during the story he acted very self-centered. He was once a politician and loved it very much. The relationship with his son, Gene, was not a good one. Due to Tom’s abuse early in life, he and Gene were never able to have a positive relationship. Gene also was never able to really stand up to his father. Probably due to a fear of him he had developed early in life. Even with this fear, Gene proved to be not be too damaged by his abusive childhood. I believe that his low self-etheme came from this upbringing. Still he had a kind of respect for his father because he...

Using Internet Behavior to Deliver Relevant Television Commercials

INTMAR-00124; No. of pages: 11; 4C: Available online at www. sciencedirect. com Journal of Interactive Marketing xx (2013) xxx – xxx www. elsevier. com/locate/intmar Using Internet Behavior to Deliver Relevant Television Commercials Steven Bellman a,? & Jamie Murphy b, d & Shiree Treleaven-Hassard a & James O'Farrell c & Lili Qiu c & Duane Varan a a Audience Research Labs, Murdoch University, 90 South Street, Murdoch, WA 6150, Australia Australian School of Management, Level 1, 641 Wellington Street, Perth, WA 6000, Australia Business School, University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia dCurtin Graduate School of Business, 78 Murray Street, Perth, WA 6000, Australia b c Abstract Consumer footprints left on the Internet help advertisers show consumers relevant Web ads, which increase awareness and click-throughs. This â€Å"proof of concept† experiment illustrates how Internet behavior can identify relevant television commercials that increase ad-effectiveness by raising attention and ad exposure. Product involvement and prior brand exposure, however, complicate effective Internet-targeting. Ad relevance matters more for low-involvement products, which have a short pre-purchase search process.For the same reason, using Web browsing behavior to make inferences about current ad relevance is more accurate for low-involvement products. Prior brand exposure reduces information-value, even for relevant commercials, and therefore dampens ad relevance's effect on attention and ad exposure.  © 2013 Direct Marketing Educational Foundation, Inc. Published by Elsevier Inc. All rights reserved. Keywords: Consumer search behavior; Advertising; Ad relevance; Product involvement; Behavioral targeting; Attention; Ad avoidance; Television; Internet; Experiment; Heart rate IntroductionTelevision, declining in value for advertisers in recent years, is shrinking as a mass medium due to the proliferation of networks and consequent audience fragmentation. At the same time, digital video recorders (DVRs) simplify TV ad avoidance (Wilbur 2008). Finally, advertising budgets are shifting to other media such as the Internet, where interest-based targeting has increased banner ad effectiveness by 65% (Goldfarb and Tucker 2011). Addressability, heralded decades ago, uses technology to track customer preferences and subsequently tailor advertising (Blattberg and Deighton 1991).Sending ads only to interested households improves advertising's value for consumers by increasing its relevance, and for advertisers by reducing wastage (Gal-Or and Gal-Or 2005; Gal-Or et al. 2006; Iyer, Soberman, and Villas-Boas 2005). Advertising addressability ? Corresponding author. E-mail addresses: s. [email  protected] edu. au (S. Bellman), jamie. [email  protected] com (J. Murphy), [email  protected] com (S. Treleaven-Hassard), [email  protected] com (J. O'Farrell), lili. [email  protected] edu. au (L. Qiu), [email  protecte d] com (D. Varan). based on consumer Web behavior could apply to other media nd devices such as television, smart phones, tablet devices and satellite radio (Shkedi 2010). Although search engine keywords and online social network data could augment targeting based on Web browsing behavior (Delo 2012; Jansen and Mullen 2008; Jansen et al. 2009), this addressable advertising â€Å"proof of concept† paper uses solely Web browsing behavior. Currently, TV advertisers target relevant commercials based on location, lifestyle and purchasing information (Marcus and Walpert 2007). A cable company, for instance, might use subscriber information to send different ads to different ethnic groups (Vascellaro 2011b).But information in these databases can be months or years old. Current product and brand interest based on Internet behavior could add a new layer to a targeting database. Nearly all (85%) of the United States population are Internet users (Pew Internet and American Life Project 2012), leaving digital footprints that suggest product interest. Cable companies that package cable and broadband Internet services, Comcast for example, could align household Internet and TV-viewing data to increase the relevance of marketing communication. The basic intuition behind targeting TV ads based on Web rowsing behavior is that time spent browsing pages in a 1094-9968/$ -see front matter  © 2013 Direct Marketing Educational Foundation, Inc. Published by Elsevier Inc. All rights reserved. http://dx. doi. org/10. 1016/j. intmar. 2012. 12. 001 Please cite this article as: Steven Bellman, et al. , Using Internet Behavior to Deliver Relevant Television Commercials, Journal of Interactive Marketing (2013), http:// dx. doi. org/10. 1016/j. intmar. 2012. 12. 001 S. Bellman et al. / Journal of Interactive Marketing xx (2013) xxx–xxx 2 certain product category increases interest in commercials for brands in that category.This intuition needs empirical testing, and the lite rature on consumer search suggests that differences among product categories may complicate applying this intuition (Richins and Bloch 1986). This paper opens with our conceptual framework, which distinguishes ad relevance from product involvement (Batra and Ray 1983). Consumers tend to use an ongoing search process (Bloch and Richins 1983) for high-involvement products; buying the wrong brand entails greater financial, social, or psychological risks than for low-involvement products (Rossiter and Percy 997). Internet shopping strategies differ, therefore, between high- and low-involvement products (Moe 2003). These differences in involvement, along with prior brand exposure, lead to four hypotheses about the effects of TV ad relevance discovered via Web-browsing behavior. After a discussion of the methodology and results, the paper closes with implications, limitations and future research avenues. Conceptual Framework Ad Relevance and the Consumer Search Process Advertising has rel evance before, during, and after purchase (Vakratsas and Ambler 1999).Consumer pre-purchase search has two phases, exploratory and goal-directed search (Janiszewski 1998). Consumer information needs change from generic product information (e. g. , hotels) to brand-specific information (e. g. , Hilton), including advertising by these brands (Rutz and Bucklin 2011). In St. Elmo Lewis' classic AIDA model (Strong 1925), exploratory search begins with awareness; consumers first recognize their need for a product. As interest grows, they explore options in the category and seek information from friends and the media, including the Internet. In the later oal-directed search phase, they desire a particular product or brand. Finally, they put that desire into action and buy a specific brand. Ad relevance for a product is highest during goal-directed search, lower during exploratory search, and practically non-existent with consumers unaware of a product need. Product Involvement and Web Brow sing Behavior Moe (2003) illustrates how useful matching ads to Web browsing behavior can be, and the complications associated with product involvement. Most products are low-involvement, attracting attention only during the pre-purchase search process (Bloch and Richins 983). Since pre-purchase search for these products generally ends in a purchase, the search process for low-involvement products has an immediate purchasing horizon. But the risks associated with high-involvement products lead many consumers, especially product enthusiasts, to engage in ongoing search, to continuously update their knowledge or just for enjoyment (Richins and Bloch 1986). Examples of such products include automobiles, computers, and fashion items (see Table 2 later). A search for information about a high-involvement product may not end in a purchase, and often has a future urchasing horizon. Moe (2003) used two dimensions, low versus high ad relevance (exploratory vs. goal-directed search) and low ve rsus high involvement (immediate vs. future purchasing), in a 2 ? 2 matrix to define four Web browsing strategies used by Internet shoppers (Table 1). Moe (2003) categorized visitors to a real store's Web site, which sold nutrition products such as vitamins, into these four strategies. Shoppers interested in a low-involvement product with an immediate purchasing horizon adopt a hedonic browsing strategy during exploratory search, and advertising has low relevance.They use the directed buying strategy during goal-directed search, and advertising has high relevance. Shoppers use the other two strategies for a high-involvement product with a future purchasing horizon. Advertising for high-involvement products should have relatively lower relevance for shoppers using the exploratory knowledge building strategy, compared to shoppers using the goal-directed search/ deliberation strategy. Table 1 also reports the average Web browsing time for these four strategies. These data suggest that long versus short Web browsing time can signal high ad relevance for low-involvement products.Directed buyers averaged over 36 minutes visiting the online store. In contrast, hedonic browsers spent one fifth as much time on the site, about seven minutes. Long versus short Web browsing time, however, may not signal high ad relevance for high-involvement products. First, average Web browsing time is nearly 3? times longer for high- rather than low-involvement products due to the ongoing nature of search for these products (Richins and Bloch 1986). Second, Moe's (2003) data suggest that the opposite pattern of Web browsing times will indicate low versus high ad relevance for high-involvement products.In line with theory that predicts an inverse-U effect of product experience on search activity (Moorthy, Ratchford, and Talukdar 1997), knowledge-building shoppers (low ad relevance) recorded the longest Web browsing times, nearly two hours in a single session. Shoppers with a search/delib eration strategy (high ad relevance) and extensive category knowledge focus their search time on specific products or brands and record relatively shorter Web browsing times, about the same duration as directed buyers. Table 1 Influence of ad relevance and product involvement on Web browsing behavior. Product involvementAd relevance Low (exploratory search) Low (immediate purchasing horizon) High (future purchasing horizon) High (goal-directed search) SHORT Hedonic browsing (6:41) LONG Knowledge building (111:47) LONG Directed buying (36:33) SHORT Search/ deliberation (37:59) NOTE—Adapted from Moe (2003). Numbers in parentheses are the average Web site browsing time for each of the four Internet shopping strategies (minutes:seconds). Please cite this article as: Steven Bellman, et al. , Using Internet Behavior to Deliver Relevant Television Commercials, Journal of Interactive Marketing (2013), http:// dx. doi. org/10. 1016/j. ntmar. 2012. 12. 001 S. Bellman et al. / Journal o f Interactive Marketing xx (2013) xxx–xxx The next section uses this conceptual framework to propose four hypotheses about the effects of ad relevance, indicated by Web browsing behavior, on attention and ad exposure. Hypotheses Moderating Effect of Product Involvement According to the conceptual framework above, Web browsing behavior can suggest ad relevance. A long time browsing information about a product indicates a consumer likely in goal-directed search for that product; brand advertising has high relevance, but only for low-involvement products.For highinvolvement products, Web browsing behavior is unrelated to ad relevance, or the opposite pattern, short rather than long Web browsing time, is likely to signal greater ad relevance. When advertising is relevant, that is, a consumer is in the goal-directed phase of product search, a TV commercial for that product should receive above average attention. When people pay attention to external stimuli, their heart rate goes down, most likely to minimize interference with information-intake (Lacey 1967). In other words, greater attention to relevant ads will associate with a decrease in heart rate.Ad relevance should also increase ad exposure, by reducing ad avoidance. As viewers may avoid TV commercials mechanically by channel-changing or fast-forwarding, addressable commercials interest TV advertisers as a method to combat ad avoidance. This ad exposure is better measured in viewing time, which conveys more information than a simple binary measure of ad avoidance (Gustafson and Siddarth 2007). Single-source data that match a household's commercial viewing time to its purchase history suggests viewers are more likely to watch relevant ommercials, that is, commercials for products the household buys, as opposed to irrelevant commercials (Siddarth and Chattopadhyay 1998). A recent field trial found that addressable TV ads can reduce ad avoidance by 32% (Vascellaro 2011a). Less ad avoidance means longer v iewing times for commercials, and therefore high ad relevance commercials will increase ad exposure. According to the conceptual model in Table 1, high versus low product involvement is likely to moderate the reliability of Web browsing time as an indicator of high versus low ad relevance, attention, and ad exposure.High involvement with a product is likely to translate into high interest in advertising by brands of that product during both exploratory and goal-directed search. For high-involvement products, therefore, TV commercials could have high ad relevance, attention, and ad exposure, whether or not Web browsing behavior has been recently observed. Furthermore, for high-involvement products, short rather than long Web browsing time could indicate relatively greater ad relevance. Consumers, however, are less likely to seek information online or offline about low-involvement products (Bloch andRichins 1983; Bloch, Sherrell and Ridgway 1986). This suggests that Web browsing for l ow-involvement products is highly valuable for behavioral targeting, as pre-purchase search for these products is for an immediate need (Moe 2003). For low-involvement products, Web browsing behavior should be a 3 highly reliable indicator of ad relevance, attention and ad exposure for TV commercials, but this will not be the case for high-involvement products. Thus, product involvement will moderate the effects of ad relevance indicated by Web browsing behavior: H1.Ad relevance based on Web browsing behavior will increase attention to commercials for low-, but not for high-involvement products. H2. Ad relevance based on Web browsing behavior will increase ad exposure to commercials for low-, but not for high-involvement products. Moderating Effect of Prior Brand Exposure Another variable likely to moderate addressability effects is prior exposure to advertising for a brand. Prior brand exposure reduces a commercial's information value, even when that information is relevant (Campbe ll and Keller 2003; Pechmann and Stewart 1989).Prior exposure should therefore reduce a viewer's willingness to pay attention to the commercial (Potter and Bolls 2012), or to choose ad exposure over ad avoidance (Bellman, Schweda, and Varan 2010; Woltman Elpers, Wedel, and Pieters 2003). Hypotheses 3 and 4 predict that prior brand exposure moderates the effects of ad relevance and involvement on attention and ad exposure: H3. Prior brand exposure reduces the effect of ad relevance on attention to commercials for low-involvement products. H4. Prior brand exposure reduces the effect of ad relevance on ad exposure to ommercials for low-involvement products. The next section describes the experiment to test these four hypotheses. Methodology Overview To test the concept of using Internet behavior to deliver relevant TV commercials, this experiment drew on two seemingly unrelated lab sessions. In the first lab session, each participant's Web browsing behavior was analyzed to discover hig hly relevant products. In the second lab session, this knowledge was used to individually customize the playlist of TV commercials shown to each participant. Sample and Design The experiment was a 2 ? 2 ? 2 mixed design. Prior brand xposure (yes/no) was a between-participants factor. The â€Å"yes† group saw Web banner ads in the first lab session, exposing them to visual aspects of the TV commercials for the same brands shown in the second lab session. All TV commercials were for U. S. brands unavailable in the test market, Australia, ensuring no prior brand exposure in the â€Å"no† group. Ad relevance (high/low) and Please cite this article as: Steven Bellman, et al. , Using Internet Behavior to Deliver Relevant Television Commercials, Journal of Interactive Marketing (2013), http:// dx. doi. org/10. 1016/j. intmar. 2012. 12. 001 4 S.Bellman et al. / Journal of Interactive Marketing xx (2013) xxx–xxx A. The home page for the six high-involvement product categ ories. B. The home page for a subcategory of high-involvement products: credit cards. Fig. 1. The Web site used to unobtrusively measure interest in 12 product categories. A. The home page for the six high-involvement product categories. B. The home page for a subcategory of high-involvement products: credit cards. Please cite this article as: Steven Bellman, et al. , Using Internet Behavior to Deliver Relevant Television Commercials, Journal of Interactive Marketing (2013), http:// dx. oi. org/10. 1016/j. intmar. 2012. 12. 001 S. Bellman et al. / Journal of Interactive Marketing xx (2013) xxx–xxx product involvement (high/low) were both within-participants factors for the TV commercials shown in the second lab session. A total of 211 members of an audience panel, representative of the Australian public, earned $30 (AUD) to participate in two lab sessions totaling 90 minutes. These participants were randomly assigned to the two between-participants groups (yes, prior brand ex posure = 109, no = 102). Half the sample (49%) were women, and ages ranged from 19 to 78 years (M = 45, SD = 15).All had high levels of Internet experience (Venkatesh and Agarwal 2006). Careful procedures, such as describing the two lab sessions as separate studies, helped ensure that participants were unaware that their Web browsing behavior in the first lab session influenced the TV commercials served in the second lab session. Lab Session 1 In the first lab session, participants evaluated the fictitious â€Å"Consumer Choices† Web site (Fig. 1A), which displayed information about six high- and six low-involvement product categories, identified from published classifications (Kover and Abruzzo 1993; Ratchford 1987; Rossiter, Percy, and Donovan 991; Vaughn 1986). Each product category had three subcategories (Table 2). The five pages of content for each of these 36 subcategories were matched across products for depth, breadth and reading level to allow meaningful time-in-cat egory comparisons. Participants had four minutes to explore the six highinvolvement categories, and another four minutes to explore the six low-involvement categories (the order, high- or lowinvolvement first, was randomized). Browsing time in each category was logged. For each participant, the two product ategories (one high- and one low-involvement) browsed for the longest time were that participant's two high ad relevance categories. The two corresponding low ad relevance categories (one high- and one low-involvement) were randomly selected from the participant's categories with the shortest browsing times (e. g. , 0 seconds). For participants in the prior brand exposure group, banner advertisements were at the top of each page. In the no prior brand exposure group, a generic photo-montage of the same size occupied this ad space. Each of the 36 subcategories advertised a different brand.For each participant, one brand was chosen randomly to represent its subcategory across both s tages of the experiment (e. g. , Capital One, Fig. 1B), from the two brands available for each subcategory, a total of 72. The duration of prior exposure to a brand was the time the participant spent viewing pages of content about the brand's subcategory (i. e. , prior exposure was higher for high ad-relevance categories). Lab session 1 ended after participants completed an extensive online survey about the Web site's usability (Agarwal and Venkatesh 2002; Venkatesh and Agarwal 2006). This survey reated a 20-minute delay, realistically replicating the process of identifying ad relevance based on Web browsing behavior, and subsequently delivering a set of customized commercials to a TV set-top box. 5 Lab Session 2 Participants went to a different laboratory for the second lab session, in which they evaluated new TV programs. Participants first verified their name and date of birth displayed on the TV screen, to ensure no miss-targeting of the customized ads (Gal-Or et al. 2006). They then practiced using the TV remote control to select programs and mechanically avoid ads.Participants selected one of four new one-hour U. S. television programs—drama, comedy, reality or documentary—to evaluate for potential airing in Australia. They were told these programs had been recorded off-air in the U. S. , with ads included. This selection procedure successfully eliminated differences in program liking (Coulter 1998), which can affect advertising response (Norris, Colman, and Aleixo 2003). Each program had five ad breaks, with five 30-second ads in each break. The ads shown in the first four breaks were individually customized based on the ad relevance information discovered in the first lab session.The four test ads— for two high ad-relevance products (one high- and one low-involvement) and two low ad-relevance products (one high- and one low-involvement)—were counterbalanced across the first four breaks, always appearing in the middle positio n to avoid primacy and recency effects (Pieters and Bijmolt 1997). The remaining eight product categories each contributed two filler ads, the 16 required for the first four ad breaks. The fifth ad break, which always showed the same five filler ads, created a natural delay before measuring brand recall. While participants watched their chosen program, the two ependent variable measures were collected unobtrusively. Attention was heart rate decrease relative to each participant's pre-program baseline heart rate (Potter and Bolls 2012). The slowest heart rate during a commercial—representing the peak of attention (Lang et al. 1993)—was subtracted from the participant's slowest resting-baseline heart rate (Wainer 1991). Heart rate was measured via pulse photoplethysmography at two places: the lobule of the ear and the distal phalanx of the non-dominant hand's ring finger. The signal, ear or finger, with the fewest artifacts (mainly caused by movement) was retained.Sixty- four participants (30% of 211, women = 47%, age range 19-75 yrs) consented to this procedure and yielded usable heart rate data. None of these participants was on medication that affects heart rate (Andreassi 2007). Thanks to an efficient mixed-level design, the size of this sub-sample was sufficient to test the two attention hypotheses with 99. 9% power (Faul et al. 2007). Ad exposure was the number of seconds that the commercial displayed on the screen before avoidance. Participants avoided ads by pressing the remote control's skip button, which jumped to the next ad or program segment.In this experiment skipping was impossible during the program and during the first five seconds of each commercial, to ensure that each skip decision was on the merits of the ad rather than a general goal of avoiding all commercials. A matched sample (n = 81) confirmed that this procedure added a nonsignificant 1. 67 seconds of ad exposure, compared to participants able to skip at any time. Although previous studies have used ad viewing time to measure ad attention (Olney, Holbrook, and Batra 1991), in this study Please cite this article as: Steven Bellman, et al. Using Internet Behavior to Deliver Relevant Television Commercials, Journal of Interactive Marketing (2013), http:// dx. doi. org/10. 1016/j. intmar. 2012. 12. 001 S. Bellman et al. / Journal of Interactive Marketing xx (2013) xxx–xxx 6 Table 2 Product categories and subcategories. Involvement Category Subcategories High Automotive 1. Luxury Cars 2. Compact 4WDs 3. Sedans 4. Credit Cards 5. Financial Planning 6. Retail Banking 7. Digital Televisions 8. Computers 9. Kitchen and Laundry Appliances 10. Jewellery 11. Casual Wear 12. Sportswear 13. Home Insurance 14. Automotive Insurance 15. Life Insurance 16. Deodorant 7. Hair Care 18. Allergy Medication 19. Hamburgers 20. Mexican Food 21. Chicken 22. Household Cleaners 23. Laundry Detergent 24. Cleaning Tools 25. Gardening 26. Tools 27. Pest Control 28. Chocolate Bars 29. Mints 30. Chewing Gum 31. Soft Drinks 32. Energy Drinks 33. Coffee 34. Frozen Meals 35. Packaged Meats 36. Desserts Financial Services Technology Fashion Apparel Insurance Health & Well-Being Low Fast Food Home Cleansers Home Maintenance Candy Beverages Packaged Food NOTE—For every subcategory, two brands were available for selection (i. e. , 72 brands). attention and ad exposure were uncorrelated (r = ? 06, p = . 665), justifying the use of both measures. After watching the one-hour program, participants completed a second online survey on the same flat screen monitor used to watch the program. In line with the cover story for lab session 2, this survey began by measuring program liking (Coulter 1998; Cronbach's alpha = . 96). The survey went on to measure manipulation checks of ad relevance and product involvement, and managerially relevant outcomes associated with greater attention and ad exposure (see the Appendix A). After completing this survey, participants w ere debriefed, hanked, and given their gift-card. products for which they were in the goal-directed search phase. This was confirmed by significant differences in self-reported purchasing horizon, measured in the post test (Table 3). Products classified as high ad-relevance, based on Web browsing time, were more likely to be used or purchased in the next month than those classified as low ad-relevance (Mlow ad-relevance = 3. 65 times per month vs. Mhigh ad-relevance = 6. 78). As predicted by the conceptual framework in Table 1, a significant two-way interaction between ad relevance and product involvement ualified this Internet-targeting main effect (Table 3). Using Web browsing time, ad relevance was inferred more accurately for low- rather than high-involvement products. For high-involvement products, purchase/usage was more likely for products inferred as low ad-relevance, based on Web browsing time (Mlow ad-relevance = . 20 times per month vs. Mhigh ad-relevance = . 10). Failure to observe Web browsing did not indicate low ad-relevance for high-involvement products, and as shown in Table 1, short rather than long Web browsing time could indicate relatively greater ad relevance.Also in line with Table 1, low-involvement products had a significantly shorter purchasing horizon compared to highinvolvement products (Mlow-involvement = 10. 28 times per month vs. Mhigh-involvement = . 15; Table 3). Product Involvement The manipulation of product involvement was also successful, measured by self-reported product involvement (Mlow-involvement = 4. 02 [on a 7-pt scale] vs. Mhigh-involvement = 4. 93, p b . 001, partial ? 2 = . 27), even without individual customization. No other effects were significant (e. g. , ad relevance: Mlow ad-relevance = 4. 40 vs.Mhigh ad-relevance = 4. 55, p = . 213, partial ? 2 = . 007). Table 3 ANOVA results. Effect Within-participants effects Ad relevance Product involvement Purchasing horizon (monthly frequency) Attention (heart rate dec rease) Ad exposure (viewing time in seconds) 10. 08** (. 05) 122. 15*** (. 37) 10. 78** (. 05) 1. 26 (. 01) .19 (. 001) 1. 40 (. 01) 3. 67 †  (. 06) 1. 34 (. 02) 1. 64 (. 03) 2. 17 (. 03) .27 (. 004) 4. 64* (. 07) 7. 14** (. 03) 2. 42 (. 01) 1. 90 (. 01) .38 (. 002) 2. 47 (. 01) 1. 02 (. 005) .17 (. 001) 209 .01 (b . 001) 62 .56 (. 003) 209 Independent Variable ChecksAd relevance ? product involvement Ad relevance ? prior brand exposure Product involvement ? prior brand exposure Ad relevance ? product involvement ? prior brand exposure Between-participants effect Prior brand exposure via Web banner ads Error degrees of freedom Ad Relevance The validity of the ad relevance factor depends critically on whether participants spent more time in lab session 1 looking at NOTES—F ratios (hypothesis degrees of freedom = 1). Numbers in parentheses are effect sizes (partial ? 2): small = . 01, medium = . 06, large = . 14. Significant effects in bold. p = . 06, * p b . 05, ** p b . 01, *** p b . 001. Results Please cite this article as: Steven Bellman, et al. , Using Internet Behavior to Deliver Relevant Television Commercials, Journal of Interactive Marketing (2013), http:// dx. doi. org/10. 1016/j. intmar. 2012. 12. 001 S. Bellman et al. / Journal of Interactive Marketing xx (2013) xxx–xxx Fig. 2B shows that, in line with H1, ad relevance based on Web browsing time increased attention to commercials for low-, but not for high-involvement products. Attention was measured by heart rate decrease (HRD): the greater the ecrease, the more attention to the commercial. But H1 was only partially supported, as this effect was significant only without prior brand exposure (H1 in Table 4), as predicted by H3 (see below). The effect of ad relevance on ads for low-involvement products generated a marginally significant main effect of ad relevance on attention (Tables 3 and 4). Similarly, planned contrasts (Winer 1991) showed that in line with H2, ad relevance based on Web browsing time increased ad exposure to commercials for low-, but not for high-involvement products (Fig. A and H2 in Table 4). Ad exposure was measured by ad viewing time: how much of an ad was seen before pressing the skip button. A longer ad viewing time means more ad exposure and less ad-avoidance. This effect delivered a significant effect of ad relevance even after collapsing across low- and high-involvement products (Table 3). Moderating Effects of Prior Brand Exposure: Hypotheses 3 and 4 The effect of ad relevance on attention to commercials for low-involvement products predicted by H1 was qualified by the significant three-way interaction predicted by H3, among ad elevance, product involvement and prior brand exposure (Table 3). Prior brand exposure reduced the effect of ad relevance on attention to commercials for low-involvement products, most likely because prior brand exposure reduced their information-value. After prior brand exposure, viewers paid equal attenti on to the test commercials, no matter what their ad relevance (Fig. 2B and H3 in Table 4). Prior brand exposure also reduced the effect of ad relevance on ad exposure to commercials for low-involvement products, as predicted by H4. After prior brand exposure, ad exposure DiscussionThis study tested the effectiveness of Internet-targeted TV advertising, using recent Web browsing to identify a household's relevant TV commercials. The results suggest that this method of Internet-targeting significantly increases attention and ad exposure, even when based only on Web browsing behavior rather than search-engine keywords. These results echo similar field trials of addressable TV ads (Vascellaro 2011a) and single-source data (Siddarth and Chattopadhyay 1998), which have shown how ad relevance can increase TV ad exposure. However, these results also show that product nvolvement and prior brand exposure complicate Internettargeting of TV commercials. First, the overall effect of Internet-tar geting on ad exposure in this study was due solely to its effect on commercials for A. No Prior Brand Exposure -5 Attention (heart rate decrease [bpm]) Effects of Ad Relevance: Hypotheses 1 and 2 was not significantly longer for high- versus low ad-relevance commercials for low-involvement products (Fig. 3B and H4 in Table 4). The results of the four hypothesis tests are summarized in Table 5. -6 -5. 84 -7 -8 -7. 88 -8. 43 -9 -9. 11 -10 Low Ad Relevance -11 High Ad Relevance -12Low High Product Involvement B. Prior Brand Exposure -5 Attention (heart rate decrease [bpm]) Prior Brand Exposure Prior brand exposure, via Web banner ads, increased brand recall but not significantly (Mno = 4. 3% vs. Myes = 6. 8%, p = . 132, partial ? 2 = . 011). Prior brand exposure did, however, have a significant two-way interaction with ad relevance (p = . 017, partial ? 2 = . 027). When prior brand exposure was present, brand recall was significantly higher for high versus low ad-relevance TV commercia ls (Mlow ad-relevance = 3. 2% vs. Mhigh ad-relevance = 9. 6%, p = . 016, partial ? 2 = . 053).When prior brand exposure was absent, brand recall was not significantly different for high versus low ad-relevance commercials (Mlow ad-relevance = 5. 4% vs. Mhigh ad-relevance = 3. 9%, p = . 441, partial ? 2 = . 006). Since ad relevance was determined by Web browsing time, participants who recorded zero browsing times for their low ad-relevance categories had no prior brand exposure. No other effects were significant. In particular, prior brand exposure did not interact with product involvement, suggesting no differences in cognitive avoidance of Web banner ads in the first lab session for lowversus high-involvement products. -6 -7 -8 -7. 76 -8. 07 -7. 84 -8. 51 -9 -10 Low Ad Relevance -11 High Ad Relevance -12 Low High Product Involvement Fig. 2. The effects of ad relevance and product involvement on attention to TV commercials, measured by heart rate decrease, for the two prior brand ex posure groups: (A) no prior brand exposure, and (B) prior brand exposure via Web banner ads. Please cite this article as: Steven Bellman, et al. , Using Internet Behavior to Deliver Relevant Television Commercials, Journal of Interactive Marketing (2013), http:// dx. doi. org/10. 1016/j. intmar. 2012. 12. 001 S. Bellman et al. Journal of Interactive Marketing xx (2013) xxx–xxx 8 Table 4 Cell means. Low ad relevance Variable ? 7. 55†  Attention (heart rate decrease) No prior brand exposure Prior brand exposure Ad exposure (viewing time in seconds) No prior brand exposure Prior brand exposure High ad relevance Test Low product High product Low product High product involvement involvement involvement involvement H1 ? 6. 95 ? 7. 13x ? 5. 84x H3 ? 7. 96 ? 8. 07 H2 19. 99x 19. 18x ? 8. 32†  ? 8. 43 ? 8. 44 ? 8. 49x ? 9. 11x ? 7. 88 ? 7. 84 ? 8. 14 ? 7. 76 ? 8. 51 20. 79 21. 23x 21. 22x 21. 25 19. 48x 18. 79x H4 8. 14 ? 8. 19 20. 16 21. 01x 21. 70x 20. 33 20. 50 19. 58 21. 42 21. 46 20. 75 22. 17 NOTES—Means in the same row with the same superscript letters differ significantly (p b . 05) using planned contrast tests (except: †  p b . 06). which in turn increases ad liking (r = . 25, p b . 001). Although consumers have privacy concerns about targeted advertising (Spangler, Hartzel, and Gal-Or 2006), these concerns about Internet-targeted TV commercials could be alleviated if these commercials displayed the Digital Advertising Alliance's Advertising Choices Icon and viewers could opt out from eceiving these commercials (youradchoices. com). For advertisers, these results support the concept of using Internet-targeting to reduce wastage in advertising budgets. Internet targeting also increases the effectiveness of TV commercials, by increasing ad exposure, which increases brand recall (r = . 14, p b . 05) and purchase intention (r = . 34, p b . 001). The results also show that Internet targeting is more critical for advertising low-involvem ent products, such as food, as opposed to high-involvement products like durables. Although changing the habitual nature of low-involvement onsumption is hard, commercials for low-involvement products may often suffer from bad timing. To combat this, many advertisers use continuous advertising (Ephron 1995), which is expensive and counterproductive by increasing prior brand exposure. Internet-targeting provides a way of continually monitoring household interest in low-involvement products, showing ads only when they are relevant and minimizing prior exposure. Relevance for habitual purchases, for which the A. No Prior Brand Exposure Implications Ad Exposure (ad viewing time [seconds]) 25 21. 70 20 0. 16 20. 33 18. 79 15 Low Ad 10 Relevance 5 High Ad Relevance 0 Low High Product Involvement B. Prior Brand Exposure Ad Exposure 30 (ad viewing time [seconds]) low-involvement products. But targeting-accuracy may not matter for high-involvement products, such as durables. Meta-analysis sh ows that advertising is more effective, on average, for durables rather than non-durables (Sethuraman, Tellis, and Briesch 2011). Consumers often gather information about high-involvement products they are not planning to purchase immediately (Moe 2003; Richins and Bloch 1986).Commercials for high-involvement products attract consistently high levels of attention and ad viewing time, as sources of information during the ongoing search process for these products. For this reason, ad-relevance can be high for high-involvement products, whether or not Web browsing behavior is observed. Second, prior brand exposure reduces the information-value of advertising (Campbell and Keller 2003). Consumers pay less attention to TV commercials, evaluate them more negatively, and are more likely to avoid them (Bellman, Schweda, and Varan 2010; Woltman-Elpers, Wedel, and Pieters 2003).In this study, prior brand exposure dampens the effects of ad relevance and product involvement. Relevant commercial s for low-involvement products receive more attention and ad exposure only when prior brand exposure is not present. 30 25 20 19. 58 20. 75 21. 42 22. 17 15 Low Ad 10 Relevance 5 High Ad Relevance 0 For consumers, the results of this study suggest that Internet targeting can improve their TV viewing experience. Internet targeting increases ad relevance, which means TV commercials are worth watching rather than avoiding. In this study, greater ad relevance due to Internet targeting increases ad exposure, Low HighProduct Involvement Fig. 3. The effects of ad relevance and product involvement on ad exposure, measured by ad viewing time for the two prior brand exposure groups: (A) no prior brand exposure, and (B) prior brand exposure via Web banner ads. Please cite this article as: Steven Bellman, et al. , Using Internet Behavior to Deliver Relevant Television Commercials, Journal of Interactive Marketing (2013), http:// dx. doi. org/10. 1016/j. intmar. 2012. 12. 001 S. Bellman et al. / Journal of Interactive Marketing xx (2013) xxx–xxx Table 5 Results of hypothesis tests. Hypothesis Accepted? H1. Ad relevance, based on Web browsing ehavior, will increase attention to commercials for low-, but not for high-involvement products. H2. Ad relevance, based on Web browsing behavior, will increase ad exposure to commercials for low-, but not for high-involvement products. H3. Prior brand exposure reduces the effect of ad relevance on attention to commercials for low-involvement products. H4. Prior brand exposure reduces the effect of ad relevance on ad exposure to commercials for low-involvement products. PARTIALLY (with no prior brand exposure) YES YES YES household does not search online, might be determined by knowledge of the household's shopping cycle.For advertisers of high-involvement products, ad timing is less critical, and traditional databases derived from cable subscription data, or warranty cards, seem adequate for targeting. And advertising still pla ys a role outside the consumer search process, most importantly to create awareness and interest in new purchases (Vakratsas and Ambler 1999). Conclusions Limitations withstanding, this study demonstrates how Webbased targeting can deliver the right TV commercial to the right person, and at the right time. Timeliness is particularly important for low-involvement products, as their relevance may change aily or even hourly. Timely Internet activity data can help TV advertisers identify commercials that currently interest a consumer. Digital-targeting's potential heightens as individuals and households increasingly add devices and applications for online multi-tasking (Pilotta and Schultz 2005). This article illustrates a viable technique to tempt marketing practitioners and academics, and fuel information privacy concerns. A framework for information privacy research builds on three broad dimensions: (1) multiple publics, (2) information channel developments, and (3) public responses to privacy ctions (Peltier, Milne, and Phelps 2009). Failure to address privacy concerns is one of several limitations to this study and a promising future research avenue. Limitations and Future Research Suggestions This study's main limitation is customizing ad relevance individually rather than group-wise (Richins and Bloch 1986) in order to test the concept of Internet targeting. Individual differences provide alternative explanations and add noise to the observed ad relevance effect (Cook and Campbell 1979). Using over 30 product subcategories helps distribute this noise evenly. The procedure in this article resembles how Fazio et al. 1986) investigated attitude accessibility. In two experiments, they individually customized a list of 16 attitude objects on the 9 basis of each participant's reaction times in a pretest, and validated this procedure in a third experiment by obtaining identical results using manipulated stimuli. Future experiments could use a similar procedure to manipulate ad relevance (Perkins and Forehand 2012). Another limitation is using Web-browsing rather than search-engine keywords to identify ad relevance. Parameters for the former were more feasible for a controlled experiment (e. g. only 72 commercials were needed). However, searchengine queries provide a more direct and accurate means of identifying the consumer's stage in the search process (Rutz and Bucklin 2011). Future studies may find the benefits of using search-engine queries are greater (Langheinrich et al. 1999). Internet-based targeting for high-involvement products might be improved by using search-engine queries, and more sophisticated analysis of Web browsing behavior. For example, Cai, Feng, and Breiter (2004) identify travel sites as highly relevant when a visitor views pages conveying specific as pposed to general information. Moe (2006) demonstrates how clickstream data can be used to infer both the stage of the decision process and the decision rule, which toget her might help identify abnormally high ad relevance for highinvolvement products. This study used ad viewing time as a measure of ad exposure. But in other studies, especially field studies, the relationship between ad viewing time and effectiveness may not be positive (cf. Tse and Lee 2001). For example, Greene (1988) observed that an ad avoider in the field â€Å"has to really watch the set to see/know/perceive what she or he is doing nd ends up with more commercial exposure value† (p. 15). Future studies should attempt to replicate these findings in field trials. Also, ad exposure may have nonlinear threshold effects, 1 or be affected by differences between commercials (Woltman Elpers et al. 2003). A promising future research avenue is experimentally manipulating the content of ads (e. g. , Teixera, Wedel, and Pieters 2010), as well as their ad relevance. Ideally, other psychophysiological measures of attention (Potter and Bolls 2012) could have been used but in the curre nt setting eart rate was the least invasive. The manipulation of prior brand exposure was too weak to generate a main effect on explicit memory, but did have a significant interaction effect. The explanation is most likely that prior brand exposure was manipulated by the presence of Web banner ads and these ads tend to be processed preattentively or cognitively avoided (Chatterjee 2008; Dreze and Hussherr 2003). Future studies could manipulate prior exposure using more attention-getting stimuli, such as brand integrations in Web site editorial. If Web banners are used, implicit measures 1For example, brand recall may require a minimum ad exposure equal to 70% of an ad's duration (21 s for a 30 s ad). To test for a non-linear threshold effect of ad exposure on brand recall, ad exposure was categorized into ? ve bins, 0–9 s, 10–15 s, 16–21 s, 22–25 s, and 26–30 s. This analysis revealed only a signi? cant linear trend (p b . 001, partial ? 2 = . 040) in the means for these bins: 0%, 1. 6%, 2. 5%, 3. 9%, 10. 5%. This result may have differed, however, if the study had measured message recall. The authors thank an anonymous reviewer for suggesting this analysis. Please cite this article as: Steven Bellman, et al. Using Internet Behavior to Deliver Relevant Television Commercials, Journal of Interactive Marketing (2013), http:// dx. doi. org/10. 1016/j. intmar. 2012. 12. 001 10 S. Bellman et al. / Journal of Interactive Marketing xx (2013) xxx–xxx of banner ad effectiveness could be used as manipulation checks (Perkins and Forehand 2012). A final limitation of this study is investigating the effect of targeting ads solely by interest in a product category. Future studies could examine the effects of other personalization strategies, such as interest in specific brands, programs, creative execution styles, and offers (Verhoef et al. 010). Each of these strategies merits evaluation and comparison in order to determine effecti ve methods of targeting addressable TV advertising. Acknowledgments The authors would like to thank the editor and the two anonymous reviewers for their constructive feedback during the review process. The authors are also grateful to Adrian Duffell, Karl Dyktinski, Emily Fielder, Michael Gell, Shannon Longville, and a team of research assistants for their considerable help in conducting the experiment reported here. This research was funded by the sponsors of the Beyond: 30 project (www. beyond30. org). Appendix A.Manipulation-checks and other measures In addition to the two unobtrusive measures of attention and ad exposure collected during lab session 2, which were the main dependent variables, an online survey at the end of the second lab session collected self-report measures of manipulation checks and managerially relevant outcome measures. Except for product involvement (Mittal 1995; alpha = . 97), the survey used validated single-item measures (e. g. , ad liking; Bergkvist an d Rossiter 2007). To accommodate the slightly different question wording required for each of the 72 brands, plus selecting only the articipant's four test brands to ask questions about, the survey did not use a random order of questions, but the following fixed, minimally biasing order (Rossiter and Percy 1997). Brand recall (unaided correct brand recall = 1, else = 0) was measured after program liking. Purchase intention was measured next, using Juster's (1966) 11-point scale for high-involvement products and Jamieson and Bass's (1989) 5-point scale for low-involvement products. Ad liking was next, followed by product involvement, and finally purchasing horizon: purchase/usage frequency per month, measured by different 8-point scales for low- and igh-involvement products (low: â€Å"never† to â€Å"3 or more times a day†; high: â€Å"do not plan to purchase† to â€Å"within the next month†; Goldberg and Gorn 1987). 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