CONSUMER BEHAVIOR IN DIGITAL MARKETS

AN ABSTRACT OF THE RESEARCH PAPER OF JOHN QUIGLEY, for the M.S. degree in MASS COMMUNICATION AND MEDIA ARTS, presented on APRIL 3, 2015, at Southern Illinois University Carbondale. TITLE: CONSUMER BEHAVIOR IN DIGITAL MARKETS Advancements in technology have reshaped the way we behave as consumers. Today’s commerce is turning digital. Consumers are becoming more aware of electronic commerce and the security concerns that come with e-commerce. This study will outline the differences of traditional commerce and electronic commerce, and how and why it is changing the market place. A survey was also completed, a sample of 66 undergraduates. Showed a positive outlook on the future of e-commerce. A little over half “57.8%” responded saying they still find it difficult to spend a vast amount of money while purchasing a good online. This paper will outline the pros and cons of e-commerce, traditional brick and mortar businesses and consumer behavior

In Search of Information Systems (Grand) Challenges - A Community of Inquirers Perspective

The paper reports on the results of a Delphi study with 143 information systems (IS) academics that was designed to explore what IS academics perceive to be the grand challenges of the IS discipline. The results provide evidence that the scholarly IS discipline is still much concerned with itself, for instance, in terms of its identity, relevance, foundational theory, or methodological pluralism – suggesting that the old debate on IS identity is not yet overcome. It thus cannot be claimed that the study identifies the grand challenges of the discipline – still it becomes noticeable that the academic community sees potentials for the IS discipline to have societal impact. A total of 21 challenges are identified, of which six challenges are categorized as “meta challenges for further developing the IS discipline” and the remaining 15 challenges are categorized as “IS research challenges” pertaining to socio-technical systems, IS infrastructures, society and ecology, as well as social well-being and affectivity. We provide a ranking of all challenges according to their relevance, potential impact, and possible time frame of realization. The results have some important implications for IS as a discipline as well as its prospective future societal role. It is hoped that through our study we can contribute to the important debate on the challenges of the academic IS discipline

Using eCommerce to Improve Product Marketing and Profitability in Nigeria

Small and medium enterprises in Nigeria rarely use eCommerce, which has led to lagging market shares and profitability compared to firms in other countries that use eCommerce. Approximately 90% of boutique fashion businesses shut down their businesses due to the inability to operate outside their business location. The social exchange theory was used in this multiple case study to explore how some small business owners in the boutique fashion industry use eCommerce to improve product marketing and profitability in Nigeria. The target population for this study was 5 fashion boutique owners based in Lagos State, Nigeria with a significant record of profitability by using eCommerce in product marketing. The data collection was through semistructured face-to-face interviews with 5 business leaders; each from different fashion boutiques in Lagos. Data collected was first coded to maintain confidentiality of participants, the digital recordings was transcribed into a Microsoft word document, and Nvivo 10 software was used to analyze and generate emerging themes. The data analysis was supported by methodological triangulation and member checking to enhance the credibility and trustworthiness of the interpretations. Two of the themes that emerged from the study were generating sales to improve profitability and strategic store locations. Use of eCommerce may contribute to social change through an increase in successful startups, increased employment, and the positive impact such companies have in the societies and communities they operate. Leveraging eCommerce may enable small- and medium-sized enterprise leaders to operate sustainable businesses

Enhancing Workplace Productivity and Competitiveness in Trinidad and Tobago Through ICT Adoption

The productivity of Trinidad and Tobago\u27s public sector workplaces is related to their absorptive capacity for technological adoption. Guided by the technology acceptance model, which suggests that individuals\u27 and institutions\u27 use of technology increases in relation to perceived ease of use and apparent value, this case study explored how Trinidad and Tobago used information and communications technology from 2001 - 2010 to improve public sector workplace productivity. Study data were collected from 22 individual interviews with senior executives from the government of Trinidad and Tobago, members of the e-business roundtable, and local industry experts, and from reviewing the archives of the Ministry of Public Administration and Information. The data were analyzed using keyword frequency comparison, coding techniques, and cluster analysis. The resulting themes include e-legislation, e-infrastructure, e-readiness, government e-services, and e-business. The study findings showed that Trinidad and Tobago\u27s technology agenda centered primarily on connecting government ministries and agencies. It also ushered in a period of telecommunication liberalization, which provided sustainable and cost effective options for government, citizens, and businesses to access broadband technology services. The results of the study showed that this access to low-costs broadband technology provides a platform for digital inclusion by improving workplace productivity, providing access to additional opportunities for education via an online platform, and increasing employment opportunities

Ethical and Unethical Hacking

The goal of this chapter is to provide a conceptual analysis of ethical, comprising history, common usage and the attempt to provide a systematic classification that is both compatible with common usage and normatively adequate. Subsequently, the article identifies a tension between common usage and a normativelyadequate nomenclature. ‘Ethical hackers’ are often identified with hackers that abide to a code of ethics privileging business-friendly values. However, there is no guarantee that respecting such values is always compatible with the all-things-considered morally best act. It is recognised, however, that in terms of assessment, it may be quite difficult to determine who is an ethical hacker in the ‘all things considered’ sense, while society may agree more easily on the determination of who is one in the ‘business-friendly’ limited sense. The article concludes by suggesting a pragmatic best-practice approach for characterising ethical hacking, which reaches beyond business-friendly values and helps in the taking of decisions that are respectful of the hackers’ individual ethics in morally debatable, grey zones

Best Practices and Recommendations for Cybersecurity Service Providers

This chapter outlines some concrete best practices and recommendations for cybersecurity service providers, with a focus on data sharing, data protection and penetration testing. Based on a brief outline of dilemmas that cybersecurity service providers may experience in their daily operations, it discusses data handling policies and practices of cybersecurity vendors along the following five topics: customer data handling; information about breaches; threat intelligence; vulnerability-related information; and data involved when collaborating with peers, CERTs, cybersecurity research groups, etc. There is, furthermore, a discussion of specific issues of penetration testing such as customer recruitment and execution as well as the supervision and governance of penetration testing. The chapter closes with some general recommendations regarding improving the ethical decision-making procedures of private cybersecurity service providers

Enhancing Automation and Interoperability in Enterprise Crowdsourcing Environments

The last couple of years have seen a fascinating evolution. While the early Web predominantly focused on human consumption of Web content, the widespread dissemination of social software and Web 2.0 technologies enabled new forms of collaborative content creation and problem solving. These new forms often utilize the principles of collective intelligence, a phenomenon that emerges from a group of people who either cooperate or compete with each other to create a result that is better or more intelligent than any individual result (Leimeister, 2010; Malone, Laubacher, & Dellarocas, 2010). Crowdsourcing has recently gained attention as one of the mechanisms that taps into the power of web-enabled collective intelligence (Howe, 2008). Brabham (2013) defines it as “an online, distributed problem-solving and production model that leverages the collective intelligence of online communities to serve specific organizational goals” (p. xix). Well-known examples of crowdsourcing platforms are Wikipedia, Amazon Mechanical Turk, or InnoCentive. Since the emergence of the term crowdsourcing in 2006, one popular misconception is that crowdsourcing relies largely on an amateur crowd rather than a pool of professional skilled workers (Brabham, 2013). As this might be true for low cognitive tasks, such as tagging a picture or rating a product, it is often not true for complex problem-solving and creative tasks, such as developing a new computer algorithm or creating an impressive product design. This raises the question of how to efficiently allocate an enterprise crowdsourcing task to appropriate members of the crowd. The sheer number of crowdsourcing tasks available at crowdsourcing intermediaries makes it especially challenging for workers to identify a task that matches their skills, experiences, and knowledge (Schall, 2012, p. 2). An explanation why the identification of appropriate expert knowledge plays a major role in crowdsourcing is partly given in Condorcet’s jury theorem (Sunstein, 2008, p. 25). The theorem states that if the average participant in a binary decision process is more likely to be correct than incorrect, then as the number of participants increases, the higher the probability is that the aggregate arrives at the right answer. When assuming that a suitable participant for a task is more likely to give a correct answer or solution than an improper one, efficient task recommendation becomes crucial to improve the aggregated results in crowdsourcing processes. Although some assumptions of the theorem, such as independent votes, binary decisions, and homogenous groups, are often unrealistic in practice, it illustrates the importance of an optimized task allocation and group formation that consider the task requirements and workers’ characteristics. Ontologies are widely applied to support semantic search and recommendation mechanisms (Middleton, De Roure, & Shadbolt, 2009). However, little research has investigated the potentials and the design of an ontology for the domain of enterprise crowdsourcing. The author of this thesis argues in favor of enhancing the automation and interoperability of an enterprise crowdsourcing environment with the introduction of a semantic vocabulary in form of an expressive but easy-to-use ontology. The deployment of a semantic vocabulary for enterprise crowdsourcing is likely to provide several technical and economic benefits for an enterprise. These benefits were the main drivers in efforts made during the research project of this thesis: 1. Task allocation: With the utilization of the semantics, requesters are able to form smaller task-specific crowds that perform tasks at lower costs and in less time than larger crowds. A standardized and controlled vocabulary allows requesters to communicate specific details about a crowdsourcing activity within a web page along with other existing displayed information. This has advantages for both contributors and requesters. On the one hand, contributors can easily and precisely search for tasks that correspond to their interests, experiences, skills, knowledge, and availability. On the other hand, crowdsourcing systems and intermediaries can proactively recommend crowdsourcing tasks to potential contributors (e.g., based on their social network profiles). 2. Quality control: Capturing and storing crowdsourcing data increases the overall transparency of the entire crowdsourcing activity and thus allows for a more sophisticated quality control. Requesters are able to check the consistency and receive appropriate support to verify and validate crowdsourcing data according to defined data types and value ranges. Before involving potential workers in a crowdsourcing task, requesters can also judge their trustworthiness based on previous accomplished tasks and hence improve the recruitment process. 3. Task definition: A standardized set of semantic entities supports the configuration of a crowdsourcing task. Requesters can evaluate historical crowdsourcing data to get suggestions for equal or similar crowdsourcing tasks, for example, which incentive or evaluation mechanism to use. They may also decrease their time to configure a crowdsourcing task by reusing well-established task specifications of a particular type. 4. Data integration and exchange: Applying a semantic vocabulary as a standard format for describing enterprise crowdsourcing activities allows not only crowdsourcing systems inside but also crowdsourcing intermediaries outside the company to extract crowdsourcing data from other business applications, such as project management, enterprise resource planning, or social software, and use it for further processing without retyping and copying the data. Additionally, enterprise or web search engines may exploit the structured data and provide enhanced search, browsing, and navigation capabilities, for example, clustering similar crowdsourcing tasks according to the required qualifications or the offered incentives.:Summary: Hetmank, L. (2014). Enhancing Automation and Interoperability in Enterprise Crowdsourcing Environments (Summary). Article 1: Hetmank, L. (2013). Components and Functions of Crowdsourcing Systems – A Systematic Literature Review. In 11th International Conference on Wirtschaftsinformatik (WI). Leipzig. Article 2: Hetmank, L. (2014). A Synopsis of Enterprise Crowdsourcing Literature. In 22nd European Conference on Information Systems (ECIS). Tel Aviv. Article 3: Hetmank, L. (2013). Towards a Semantic Standard for Enterprise Crowdsourcing – A Scenario-based Evaluation of a Conceptual Prototype. In 21st European Conference on Information Systems (ECIS). Utrecht. Article 4: Hetmank, L. (2014). Developing an Ontology for Enterprise Crowdsourcing. In Multikonferenz Wirtschaftsinformatik (MKWI). Paderborn. Article 5: Hetmank, L. (2014). An Ontology for Enhancing Automation and Interoperability in Enterprise Crowdsourcing Environments (Technical Report). Retrieved from http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-155187