The Business Review

The Competitiveness of Urban Locations: Main Findings of a Literature Review

Alexandre Coussa, Ph.D. Candidate, University of Fribourg, Switzerland

Dr. Philippe Gugler, Professor, University of Fribourg, Switzerland

ABSTRACT

The competitiveness of cities is a topic that has attracted the attention of many researchers in recent years. The purpose of this study is to present the highlights of the recent economic literature on this issue so as to understand the determinants, objectives and policies that shape the competitiveness of urban areas. In order to provide the most objective picture possible, a systematic review of the literature published between 2015 and 2021 was conducted using the WebofScience database. It appears that in the literature, the competitiveness of cities turns around policies, objectives and facilitators which sustain one axe an interdisciplinary and sustainable vision of competitiveness and economic development, and, on the other axe, a strong inter-cities competition. The objective of this paper is to understand the recent evolution of economic thinking on urban areas' competitiveness and to determine the key issues identified along with the literature. The chosen strategy is therefore to adopt a systematic review of articles from 2015 to 2021 using WebofScience (WOS), and complement it with articles of interest identified along with the lecture. The competitiveness of cities is reviewed by analyzing the facilitators of competitiveness, the implications in terms of objectives and finally the policy and governance issues. The results of this investigation are then synthesized and discussed. The results confirm that the literature focuses on two important axes. The first one is the interdisciplinary and sustainable vision adopted by many academics, while the second one focuses on issues of competitiveness between cities. In this sense, the competitiveness of cities is strongly influenced by current issues such as neoliberalization, the development of digital technologies and sustainability considerations, such as mobility, education, ecological or social inclusion. The strategy chosen in the present work is to adopt a systematic review of articles from 2015 to 2021 by employing WebofScience, and to complement it with articles, theories, and sources of interest. The aim of a basic literature review is to develop a complete understanding of the current state of knowledge on a specific topic (Machi and McEvoy, 2008, pp. 1-3) and the present review aims to achieve the same. The approach applied in that purpose is schematized in figure 2 and developed further. The first step consists in identifying the articles relevant for the review. To do so while preserving the research of potential bias, a systematic search of scientific articles is done. WOS databases are used to identify articles wrote on the subject during the period going from 2015 to 2021. The query applied is summarized in figure 1. The aim was to identify the recent articles discussing the different aspects of cities development and competitiveness. After proceeding, 1604 articles are found, a screening of all titles and abstracts has afterwards been done to extract 308 articles relevant to the topics of cities competitiveness. In step 2, the occurrence of authors’ keywords of those 308 articles was established in order to identify the main topics discussed in the literature. The outline of the thesis had then been composed by identifying the major realms of research. Cities competitiveness is investigated through an itinerant progression by analyzing first what are the facilitators of competiveness, then the implication in terms of objectives and results for cities are reviewed. The questions of policy and governance implied by the objective and results are in a third stage studied. Following the topics chosen for review, 80 articles were removed because they addressed issues considered to be of less interest in relation to the chosen themes. Lastly, during the step 3, the literature review in itself, other articles were again excluded during a more in-depth lecture, because considered to be of no interest or not fitting the topics chosen to be developed. On the other hand, some articles were added to the database and this latter finally includes 173 articles.

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Artificial Intelligence and Product Development

Dr. Mohammed R. Ahmed, Webster University, FL

Dr. Betty E. Ahmed, Liberty University, VA

ABSTRACT

Artificial Intelligence (AI) is not a new concept. It probably existed in the minds of researchers centuries ago, but researchers began experimenting with AI with the introduction of digital technology. Introducing the microprocessor brought digital computing power to individual researchers, learners, and professionals, leading to applications of the technology in business and management. We developed analog intelligent machines in the late sixties and seventies, and the aviation industry successfully applied autopilot in flight management. The growth in AI systems has resulted from technological changes, such as computing speed, capacity, capability, and storage. It has also created opportunities to build learning machines that will help managers make decisions and improve products and services in all functional business areas. The shortening of the average product cycle, intense competition in the marketplace, and rapid technological change has created an environment where the growth and profits of the firms depend on new product development. New product development has become a key element in developing a competitive strategy. Product development decisions involve significant investments and long-term value for the company. The products in the technology-based industries have become so complex that the companies have changed their production strategy from manufacturing to sub-assembling the products. New product development at the firm level requires research and development at the suppliers' level. The supplier has to become partners in the firm's growth strategy. The study aimed to investigate the process of new product development in the rapid growth industry, analyze the firm and supplier involvement in new product development, and develop a model for formulating a new product development strategy. The proposed model links the firm, supplier, artificial intelligence, growth, and business model for developing a long-term new product development strategy. The growth in AI learning capabilities and intense competition provide an excellent opportunity to investigate the new product development process and learning machine applications. The proposed 4Cs model would be helpful for the management of new product development and for creating a competitive advantage in the marketplace. The purpose of the paper aims to share how artificial intelligence can be used in developing a new product or service. The concepts from artificial intelligence and new product development working papers are used to introduce the application of artificial intelligence in product or service development and to build a bridge between intelligent technology and product development strategy. The growth in technology alone will not help businesses solve customer problems unless it helps businesses develop improved solutions to customers' problems. Improved solutions and new product development satisfy the customers' wants and needs, generating revenue growth. This paper builds the bridge to understand the applications of AI in new products or service development. It will also include a discussion on artificial intelligence and 4C's new product or service development process and presents the applications of AI in the 4Cs process. The word artificial refers to something created by humans to replicate close to real, but it is not natural. Intelligence is the ability to solve problems using logic, apply knowledge to enhance capabilities, the capacity to learn and apply knowledge to produce desired outcomes and other skills of the mind. Artificial Intelligence (AI) is a system created by humans using digital technology that includes hardware, software, and human contributions. It has unlimited business, education, and healthcare applications because it mimics Human Intelligence (HI).

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Why do Consumers Find a Two-Sided eWOM More Helpful: A Mediation Model of Consumer’s

Attribution About the Reviewer

Dr. Sahana Sen, BMCC, City University of New York

ABSTRACT

Consumer Reviews or e-WOM has come to be accepted as an integral aspect of the information revolution impacting consumer behavior. Traditionally WOM is received from trusted family or friends. How does a consumer evaluate the opinions of an unknown “virtual” person posted in the e-WOM product reviews? Using an observation study of real world behavior and a lab experiment, we first show that a two-sided review is considered more helpful by consumers. Then using attribution theory we demonstrate that one vs. two sided reviews are likely to generate different attributions in the reader, viz. whether the reviewer’s motivation was internal or external (reviewer vs. product oriented), and these attributions mediate their attitude towards the helpfulness of the two-sided review being greater. Our findings contribute to a deeper understanding of eWOM, in particular those arising out of the anonymity and weak ties of the reviewers with the readers. For marketers, an understanding of what makes a helpful eWOM can suggest better strategies for promoting the right form of consumer reviews on their Web site. The persuasive power of word-of-mouth (WOM) on consumer decision-making has long been established (Brown and Reingen 1987; Feldman and Spencer 1965; Herr, Kardes and Kim 1991; among others). WOM information has been described as the most powerful form of marketing communications and studies have shown that users find WOM more believable than information that is commercially generated (Hutton and Mulhern 2002). In the digital age, word-of-mouth on the Web, or eWOM, has become a ubiquitous phenomena, and an integral aspect of the information revolution impacting consumers’ search and information evaluation behavior. Due to eWOM, consumers now have almost instant access to products and opinions from sources other than the marketer of the product (Lopez & Sicilia 2011; Sundermann & Raabe 2019; Sudha & Sheena 2017). In a 2019 survey on the most common purchase influence among online shoppers in the United States, 62 percent of respondents stated that online customer reviews were very helpful (Statista 2022). Many consumers report turning to consumer product reviews first, as a source of information, amongst all online resources (Lemon & Verhoef 2016; Llamas & Belk 2022) and a 2022 survey reported that 18.8% consumers will rely more on online consumer reviews if the US enters a recession (eMarketer, 2022). However, despite the above demand for eWOM, it is not without its problems – it is after all WOM received from an anonymous person, and as a famous New Yorker cartoon once said, “On the Internet, nobody knows you are a dog.” In a famous case from the early days of eWOM this anonymity was taken advantage of by no other than the CEO of Whole Foods (Stone & Richtel, NYT, July 16, 2007; WSJ July 16, 2007). The anonymity afforded by the Web allowed John Mackey under the pseudonym “Rahodeb” to post more than a thousand positive messages about his own company, and negative messages about his competition on Yahoo Finance's bulletin board (Kesmodel & Wilke, WSJ, July 12, 2007; Lewis, Denver Post, July 15, 2007). See Figure 1 below for an excerpt. Since then, along with the rise in the use of consumer reviews on one hand, the mistrust of anonymous reviews has continued to grow (DeAndrea et al. 2015). Therefore, even though e-WOM information is prolific, the issue of source-credibility and trust is a major factor in the minds of consumers determining whether or not to use e-WOM. In the physical world, word-of-mouth is received from family or friends, i.e. people who the receiver knows and has a level of trust, based upon which the receiver decides whether or not to accept the advice (Hutton and Mulhern 2002). But how does a consumer evaluate WOM coming from a virtual person? In this research we study the impact of Argument_type, viz. whether the opinions posted are one-sided or two-sided, on the evaluation of helpfulness of an eWOM review.

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The Impact of Illiquidity on Return-Order Imbalance Relation During Financial Crisis:

Example from International Investment Banks

Feng-Sou Yang, National Taiwan University, Taiwan R.O.C.

Dr. Han-Ching Huang, Chung Yuan Christian University, Taiwan R.O.C.

ABSTRACT

In this paper, we focus on the illiquid trades on international investment banks in financial crisis. Empirical results show that before Lehman Brothers’ bankruptcy, the correlation between returns and lagged-one order imbalance is basically positive, whereas after Lehman’s bankruptcy we get a much negative relationship. Moreover, before Lehman Brothers’ bankruptcy, contemporaneous order imbalances are significantly positive, and this result is strengthened after the crisis. When market liquidity is scarcer, order imbalances have a greater explanatory power in both OLS and GARCH models owing to the reduced market efficiency. In recent years, the influence and impact of liquidity is getting more and more important, and has been one of the most popular issues in modern financial market. Particularly, the concept of liquidity is highly linked to trading volume, which may be the key cut for traders to earn abnormal returns by several trading strategies. Chordia, Roll, and Subrahmanyam (2002) has provided the link between trading volume and returns. They found order imbalance as a key factor determining the stock return rather trading volume, which is absolutely guaranteed to conceal some important aspects of trading. They concluded that the order imbalance increases following market declines and vice versa, which reveals that investors are contrarians on aggregate. Also, order imbalance in either direction, excess buy or sell orders, will reduce liquidity. Stock returns are strongly affected by contemporaneous and lagged order imbalances, and will reverse themselves after high negative imbalance. Lin (2010) have assured that it is nearly not possible for traders to earn abnormal returns by exploiting the relationship between current volume and future returns in terms of highly liquid equity markets such as the NYSE. This could also be explained by Chordia, Huh, and Subrahmanyam (2007), who concluded that the NYSE market’s liquidity is strong enough to maintain a great level of market efficiency that prevents those inside information traders from earning abnormal returns. That is, the NYSE stock market could be regarded with great level of liquidity and efficiency in its nature according to the definition of Fama (1970). However, after the financial crisis in Sep 2008, lots of issues are being brought up as to whether such high degree of market efficiency continues to be maintain under such extreme circumstances where liquidity is almost sucked up during late 2008, and do new trading opportunities appear as a result, perhaps temporary, but enough for the clever speculators to take advantage of this anomaly and earn abnormal returns. In this paper, we address these questions by first providing a comprehensive survey of recent related work in the literature followed by a brief framework of our approach. Next, we discuss our data together with our ways of processing, and then we turn to the methodology of our analysis. Later, we describe the quantitative results we have obtained accompanied by a demonstration of their statistical significance. Our results show that when market liquidity is scarce, order imbalances have a greater explanatory power in both our OLS and GARCH models thanks to the reduced market efficiency. Last but not least, we provide a conclusion based on our findings and lay down the implications that, we believe, will shed new light to this much debated issue. Fama (1970) published his profound “Efficient Capital Markets” in his seminal review has the concept of market efficiency attracted much interest from a variety of researchers. Since it has been suggested that in the academic field that market is not perfectly efficient, lots of research has been done to investigate the soundness of market efficiency. For the relationship between asset pricing and the bid ask spread, Amihud and Mendelson (1986) analyze a model in which investors with different expected holding periods trade assets with different relative spreads.

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