Search results

The global market for cloud gaming is growing rapidly. How gamers evaluate the service quality of this emerging form of cloud service has become a critical issue for both researchers and practitioners. Building on the literature on service quality and software as a service, this study develops and validates a gamer-centric measurement instrument for cloud gaming service quality.

A three-step measurement instrument development process, including item generation, scale development and instrument testing, was adopted to conceptualize and operationalize cloud gaming service quality.

Cloud gaming service quality consists of two second-order constructs of support service quality and technical service quality with seven first-order dimensions, namely rapport, responsiveness, reliability, compatibility, ubiquity, smoothness and comprehensiveness. The instrument exhibits desirable psychometric properties.

Practitioners can use this new measurement instrument to evaluate gamers' perceptions toward their service and to identify areas for improvement.

This study contributes to the service quality literature by utilizing qualitative and quantitative approaches to develop and validate a new measurement instrument of service quality in the context of cloud gaming and by identifying new dimensions (compatibility, ubiquity, smoothness and comprehensiveness) specific to it.

The main aim of this study is to examine the effect of virtual store atmospheric factors on impulsive purchasing in the metaverse context.

Grounded in purposive sampling, 451 individuals with previous metaverse experience were recruited to accomplish the objectives of this research. Next, to identify both linear and nonlinear relationships, the data were analyzed using partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN) approaches.

The findings underscore the significance of the virtual store environment and online trust in shaping impulsive buying behaviors within the metaverse retailing setting. Theoretically, this study elucidates the impact of virtual store atmosphere and trust on impulsive buying within a metaverse retail setting.

From the findings of the study, because of the importance of virtual shop content, practitioners must address its role in impulse purchases via affective online trust. The study’s findings are likely to help retailers strategize and improve their virtual store presentations in the metaverse.

The discovery adds to the understanding of consumer behavior in the metaverse by probing the roles of virtual store atmosphere, online trust and impulsive buying.

Though there is consensus that mindfulness induces mindful consumption (MC), empirical testing is needed to uncover the mechanism underlying temperance behaviour in the MC model proposed by Sheth et al. (2011). The role of mindful advertising in influencing MC needs deeper investigation. The purpose of this research paper is to bridge the gap.

The relationship between mindfulness and temperance in consumption was investigated using an online simulation. Mindful advertising by Patagonia, with a message to buy less yet demand organic, fair-trade and recycled products, was introduced as a moderator in experimental group one. The second group was exposed to an aspirational advertisement of Tommy Hilfiger, symbolic of consumption-driving communication.

Not buying any brands was the uppermost preference by the participants followed by Patagonia, which used a mindful advertisement. Tommy Hilfiger was a distant third despite using an aspirational advertisement. A predictive relationship between mindfulness and temperance in consumption remained elusive.

Consumer purchase decisions favouring mindfully advertised Patagonia make a strong business case for nurturing a mindful mindset and promoting mindful behaviour. The customer-centric sustainability strategy of caring for the people and the planet beforehand should take precedence over corporate social responsibility which is usually an afterthought.

Measuring mindfulness and MC, two constructs combined in one experimental design, using a simulation built around real-life marketing communication distinguishes this research paper.

Driven by Davis’s (1989) technology acceptance model (TAM) and Westaby’s (2005) behavioral reasoning theory (BRT), the purpose of this study is to develop and test a conceptual model and examine consumers’ acceptance of artificial intelligence (AI) chatbots for apparel shopping.

Data from 353 eligible US respondents was collected through a self-administered questionnaire distributed on Amazon Mechanical Turk, an online panel. Confirmatory factor analysis and path analysis were used to test all hypothesized relationships using the structural equation model.

The results show that optimism and relative advantage of “reasons for” dimensions have a positive and significant influence on perceived ease of use (PEU), while innovativeness and relative advantage have a positive and significant influence on perceived usefulness (PUF). Discomfort and insecurity have no significant impact on PEU and PUF. However, complexity has a negative and significant impact on PEU but not on PUF. Additionally, PEU has a positive influence on PUF. Both PEU and PUF have a positive and significant influence on consumers’ attitudes toward using AI chatbots, which, in turn, affects the intention to use AI chatbots for apparel shopping. Overall, this study identifies that optimism, innovativeness and relative advantage are enablers and good reasons to adopt AI chatbots. Complexity is a prohibitor, making it the only reason against adopting AI chatbots for apparel shopping.

This study contributes to the literature by integrating TAM and BRT to develop a research model to understand what “reasons for” and “reasons against” factors are enablers or prohibitors that significantly impact consumers’ attitude and intention to use AI chatbots for apparel shopping through PEU and PUF.

The advancement of technologies has made it possible for health-care organizations to provide convenient online services that enable people to manage their health conditions. Although many studies have investigated the adoption and benefits of e-health services, there has been little focus on health-oriented behaviors after adoption, particularly in relation to service quality and user satisfaction.

This paper is based on the SOR model and service quality theories to investigate behavioral responses, including word-of-mouth, intention to use and intention to act. The authors use a partial least squares structural equation modeling analysis with 194 participants and the diabetes risk test survey in Finland.

The results show that people are willing to engage in health self-management behaviors if they intend to use the e-health service and are satisfied with it. User satisfaction can be enhanced by improving the visual appeal of the website presentation, the quality of the presented information, as well as the usability of the website, all as components of e-health services.

The authors contribute by creating a construct “intention to act,” referring to health-oriented behaviors resulting from e-health service use. In addition, this study is among the first to apply the SOR model to investigate how user satisfaction leads to intention to use, intention to act and word-of-mouth.

Drawing on organizational learning and dynamic capabilities literature, this study aims to explore how suppliers from traditional emerging economies (STEE) can acquire, assimilate and use new knowledge essential for the development of production and marketing capabilities. These capabilities then facilitate suppliers in climbing the value chain from B-to-B to B-to-C.

The study adopted a longitudinal and multiple case study design to examine the practices of suppliers operating in a traditional emerging economy setting. This study selected Pakistan textile industry as an empirical setting, which is a predominantly supplier market for global buyers. Data sources entail semi-structured interviews with top executives and senior-level managers in four case firms and secondary data obtained from diverse sources.

The study identified transitionary phases of capabilities development that are facilitated by boundary-spanning knowledge acquisition and transformation in a dynamic manner. These capabilities are essential for a supplier’s entry into downstream international markets (i.e. launching its own products/brands in the end consumers’ market).

The findings could help managers in STEEs to understand the strategic importance of supply chain ties in their learning and capabilities development. It also provides strategic insights on what, how and why involved parties do engage over an extended period of time. Moreover, the findings of this study could help other firms to know and adopt the right type of technology(s) and systems that can help them reduce the technological gap in producing and marketing market-winning products.

This study advances the recent academic discussion that focusses on learning by supplying and the value-chain movement of suppliers (i.e. B-to-C) from their B-to-B engagements. The findings identified the vital and beneficial role of long-term relationships with global value chain partners in learning and capabilities development that led to value creation in the traditional emerging economy.

This study aims to validate the link between production manipulation and a firm’s performance variability (fundamentals and stock returns). It explores whether executives' risk-taking incentives encourage production deviations around the normal level during uncertainty.

Utilizing panel data of manufacturing firms from Compustat over three decades, the study investigates production management practices during economic uncertainty. The Economic Policy Uncertainty Index (EPU) is employed as a key metric. The empirical strategy involves documenting the effect of economic uncertainty on overproduction and underproduction, examining the role of executive compensation and assessing the impact on risk.

The research finds that risk-taking incentives increase over/underproduction, particularly amplifying the extent of underproduction during uncertainty. Production deviation rises, indicating that firms take greater risk by engaging in abnormal business operations. The study’s results are robust against various econometric methods, emphasizing the influence of risk-taking incentives on corporate production decisions.

While providing valuable insights, the study acknowledges inherent limitations, including factors influencing production decisions beyond risk-taking incentives. Further research could explore additional determinants for a comprehensive understanding.

The findings highlight the potential dark side of executive compensation that motivates suboptimal risk-taking decisions, impacting risk, cost of capital and firm performance. Policymakers and compensation committees can use these insights to design efficient systems that mitigate moral hazard problems associated with productivity changes.

The study emphasizes the broader social implications of production manipulation under uncertainty. It prompts discussions on the ethical considerations of managerial opportunism, its potential consequences for stakeholders and market dynamics.

This study contributes to the literature by examining the role of economic uncertainty on production manipulation and the influence of risk-taking incentives. It extends the earnings management literature by considering real activity manipulation and emphasizing the importance of decomposing production deviation into positive and negative values.

In the light of the case study and the accompanying case study questions, the incumbent would be able to gain a comprehensive understanding on the theoretical underpinnings of retail store expansion, identify the challenges for expanding a brand into emerging markets such as India and apply various marketing strategies aimed at in-depth analysis retail expansion. Learners can further comprehend the importance of brand communication incorporated by the brand to attract its customer subset.

It was in December 2022, when Mason Chatterjee, the Indian brand head of Armani Exchange (A|X), was confronted with the managerial dilemma whether launching the second store in the city of Ahmedabad would be a right decision. Another issue that was troubling him was how to go about launching a second store in a city which was not a home to other luxury sublabels. The case study illustrates the decisional aspect of retail expansion adopted by Chatterjee, considering the distinct managerial perspectives. Chatterjee found potential in the city of Ahmedabad, owing to an increased number of high-net-worth individuals and other macro factors. The case study is primarily an outcome of research carried out at A|X store at Ahmedabad One mall, Ahmedabad, for over a fortnight in the month of February 2023. The expansion decision of Chatterjee proved to be a success in the city of Ahmedabad reaching a sales figure of INR 1 crore (US$130,344.11) in the very first month of its launch. However, he was confronted with the managerial dilemma of further expansion, just six months after the launch of the latest expansion.

The case study is intended for advanced undergraduates or postgraduate programs in management or electives such as marketing, retail management and strategic management. It has not only been specifically designed for teaching the concept of retail expansion but can also be used to integrate contexts on brand’s merchandise mix, retail positioning, visual merchandising and brand communication. The case study has an overview of each of these elements. The instructor may choose them into the context for a wider encompassing detailed lesson or particularly on the main aspect of the case.

Teaching notes are available for educators only.

CSS8: Marketing

The present study provides a comprehensive review of the advancements in five active heating modes for cold-proof clothing as of 2021. It aims to evaluate the current state of research for each heating mode and identify their limitations. Further, the study provides insights into the optimization of intelligent temperature control algorithms and design considerations for intelligent cold-proof clothing.

This article presents a classification of active heating systems based on five different heating principles: electric heating system, solar heating system, phase-change material (PCM) heating system, chemical heating system and fluid/air heating system. The systems are analyzed and evaluated in terms of heating principle, research advancement, scientific challenges and application potential in the field of cold-proof clothing.

The rational utilization of active heating modes enhances the thermal efficiency of cold-proof clothing, resulting in enhanced cold-resistance and reduced volume and weight. Despite progress in the development of the five prevalent heating modes, particularly with regard to the improvement and advancement of heating materials, the current integration of heating systems with cold-proof clothing is limited to the torso and limbs, lacking consideration of the thermal physiological requirements of the human body. Additionally, the heating modes of each system tend to be uniform and lack differentiation to meet the varying cold protection needs of various body parts.

The effective application of multiple heating modes helps the human body to maintain a constant body temperature and thermal equilibrium in a cold environment. The research of heating mode is the basis for realizing the temperature control of cold-proof clothing and provides an effective guarantee for the future development of the intelligent algorithms for temperature control of non-uniform heating of body segments.

The integration of multiple heating modes ensures the maintenance of a constant body temperature and thermal balance for the wearer in cold environments. The research of heating modes forms the foundation for the temperature regulation of cold-proof clothing and lays the groundwork for the development of intelligent algorithms for non-uniform heating control of different body segments.

The present article systematically reviews five active heating modes suitable for use in cold-proof clothing and offers guidance for the selection of heating systems in future smart cold-proof clothing. Furthermore, the findings of this research provide a basis for future research on non-uniform heating modes that are aligned with the thermal physiological needs of the human body, thus contributing to the development of cold-proof clothing that is better suited to meet the thermal needs of the human body.

The purpose of this paper is to systematically analyze the literature around regulatory compliance and market manipulation in capital markets through the use of bibliometrics and propose future research directions. Under the domain of capital markets, this theme is a niche area of research where greater academic investigations are required. Most of the research is fragmented and limited to a few conventional aspects only. To address this gap, this study engages in a large-scale systematic literature review approach to collect and analyze the research corpus in the post-2000 era.

The big data corpus comprising research articles has been extracted from the scientific Scopus database and analyzed using the VoSviewer application. The literature around the subject has been presented using bibliometrics to give useful insights on the most popular research work and articles, top contributing journals, authors, institutions and countries leading to identification of gaps and potential research areas.

Based on the review, this study concludes that, even in an era of global market integration and disruptive technological advancements, many important aspects of this subject remain significantly underexplored. Over the past two decades, research has lagged behind the evolution of capital market crime and market regulations. Finally, based on the findings, the study suggests important future research directions as well as a few research questions. This includes market manipulation, market regulations and new-age technologies, all of which could be very useful to researchers in this field and generate key inputs for stock market regulators.

The limitation of this research is that it is based on Scopus database so the possibility of omission of some literature cannot be completely ruled out. More advanced machine learning techniques could be applied to decode the finer aspects of the studies undertaken so far.

Increased integration among global markets, fast-paced technological disruptions and complexity of financial crimes in stock markets have put immense pressure on market regulators. As economies and equity markets evolve, good research investigations can aid in a better understanding of market manipulation and regulatory compliance. The proposed research directions will be very useful to researchers in this field as well as generate key inputs for stock market regulators to deal with market misbehavior.

This study has adopted a period-wise broad-based scientific approach to identify some of the most pertinent gaps in the subject and has proposed practical areas of study to strengthen the literature in the said field.