J. Theor. Appl. Electron. Commer. Res., Volume 16, Issue 6 (September 2021) – 30 articles

With the rapid growth of express delivery industry, service failure has become an increasingly pressing issue. However, there is a lack of research on express service failure risk assessment within the Failure Mode and Effects Analysis (FMEA) framework. To address the research gap, we propose an improved FMEA approach based on integrating the uncertainty reasoning cloud model and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The cloud model describing randomness and fuzziness in uncertainty environment is adopted to achieve the transformation between the qualitative semantic evaluation of occurrence (O), severity (S), and detection (D) risk factors of FMEA and the quantitative instantiation and set up the comprehensive cloud of risk assessment matrix for express delivery service failure (EDSF). The TOPSIS method calculates and ranks the relative closeness coefficients of EDSF mode. Finally, the rationality and applicability of the proposed method are demonstrated by an empirical study for the express delivery service in China. It is found that among 18 express delivery service failure modes, six service failure modes with high risk are mainly located in the processing and delivery stages, while six service failures with the relatively low risk are involved in the picking-up and transportation stages. This study provides insight on how to explore the risk evaluation of express delivery service failure, and it helps express delivery firms to identify the key service failure points, develop the corresponding service remedy measures, reduce the loss from service failures, and improve the service quality. Full article

This study investigates how the endorsements of Internet celebrities (ICs) may drive consumer trust in their marketing campaigns, and subsequently affect impulse buying in relation to luxury fashion brands. Drawing on the framework of persuasion with a particular emphasis on the role of receivers, this study identifies five main characteristics, namely, the popularity of ICs, identification, IC adoration, social distance, and the perceived fit that may contribute to promoting impulse buying. A survey was conducted with 585 followers of IC in China. The findings reveal that trust is an essential factor that affects impulse buying. Identification and perceived fit both significantly contribute to increasing impulse buying through trust. Alternatively, large social distance may impair the relationship between trust and impulse buying. We conclude with implications for marketers that luxury fashion brands should seek cooperation not only with the most popular, but also with the most relevant ICs. An IC with a humble and relatable image can earn consumers’ trust and lead to an enhanced endorsement effect. Full article

Indonesia’s e-commerce development, with growth forecast of up to USD 300 billion by 2020, encourages many e-commerce companies to create new value in their products/services. Opportunities for e-commerce start-up collaboration programs increase the opportunities for e-commerce to grow. In e-commerce, decision-making for collaborations tends to be intuitive, centralized, and does not use strategic management tools. This study aims to identify critical factors as the main consideration in collaborative decision-making between e-commerce companies and partners. The study was conducted by developing a questionnaire for decision-makers in e-commerce collaborations. The study used the TOE framework, AHP, and TOPSIS methods. As part of the research’s object, the payment method was chosen for an e-commerce company collaborative program. Based on the criteria identified against the existing framework, there are 11 critical factors. The top three criteria are (1) networks and cooperation, (2) management commitment, and (3) knowledge and expertise in digital business. Based on the TOE framework, the main priority is the provision of e-wallet payment methods, which can be done by adding service providers. While research is limited as to the factors’ priority, future studies are suggested to select other collaborative programs or develop a collaborative strategy framework. Full article

Digital transformation is a key driving force of open innovation to capture and transfer knowledge inside and outside of a company’s bounds. New challenges in organizing multiple knowledge flows imply the need for increased competences related to this paradigm of future employees. In this article, we organize and aggregate the competencies required for open innovation collaboration and develop a competence profile that organizes individual competencies in an open innovation context. Based on elements of the European Entrepreneurship Competence Framework, we delineate an OI Competence Profile and list the core competencies to manage and accelerate the inflow and outflow of knowledge. We explore this profile by comparing data from 2332 students from four European universities to find differences in the distribution of OI competencies between countries. The study contributes to understanding the individual competencies that target the future OI needs of companies necessary in the context of digital transformation. It also introduces an interdisciplinary approach to integrate the research streams of management practice, open innovation, and entrepreneurial education. Full article

The study covered by the present paper sought to look into a range of factors affecting the building of trust in brands among social media community groups. For the purpose of the present study, in order to measure the influence of visual content, the authors of the present paper investigated its visual as well as emotional characteristics while factoring in consumer engagement variables. In order to test our hypotheses, two different visual advertisements of an artificial hypothetical apparel brand were created. The robustness of the results was ensured by the findings of the representative consumer survey and a factor and regression analysis. The survey concluded that engagement with the brand-created content by social media community groups may be viewed as a proxy variable when studying the consumer confidence in a brand within consumer groups. The authors of the paper also argue that an image-based content identity does affect the engagement with the content created by a brand within the social network community groups. The difference impact of the cognitive, emotional or behavioral involvement of social media community group members onto the formation of brand trust is revealed. Full article

With the innovation of embedded devices, the concept of smart marketplace came into existence. A smart marketplace is a platform on which participants can trade multiple resources, such as water, energy, bandwidth. Trust is an important factor in the trading platform, as the participants would prefer to trade with those peers who have a high trust rating. Most of the existing trust management models for smart marketplace only provide a single aggregated trust score for a participant. However, they lack the mechanism to gauge the level of commitment shown by a participant while trading a particular resource. This work aims to provide a fine-grained trust score for a participant with respect to each resource that it trades. Several parameters, such as resource availability, success rate, and turnaround time are used to gauge the participant’s level of commitment, specific to the resource being traded. Moreover, the effectiveness of the proposed model is validated through security analysis against ballot-stuffing and bad-mouthing attacks, along with simulationbased analysis and a comparison in terms of accuracy, false positive, false negative, computational cost and latency. The results indicate that the proposed trust model has 7% better accuracy, 30.13% lower computational cost and 31.74% less latency compared to the existing benchmark model. Full article

Online shopping has developed rapidly, but recently, the sales of some online stores have suffered due to the decrease in people’s income caused by the epidemic. How to grasp the psychology and behavior of consumers and formulate effective marketing strategies is important for increasing sales. This paper puts forward a research model and eight hypotheses based on the research on the promotion situation and the types of products promoted on consumers’ impulse shopping, and uses regression analysis, t-test, stepwise regression and analysis of variance to conduct data analysis. The results show that online promotion has a significant impact on consumers’ willingness, and the anticipated regrets in different directions have totally different effect on willingness; the type of product promoted, and the impulsive characteristics of consumers play a moderating role; online promotion affects consumers’ impulsive online shopping intentions through the intermediary effect of expected regret. The influence of anticipated regrets on impulsive online shopping intention is proposed creatively, and the results also provide e-commerce merchants and customers with new insights in managing and treating online promotions. Managerial implications like controlling the duration of promotions and the number of preferential goods are put forward based on our analysis. Full article

Interest in the application of phygital marketing to retail commerce has increased in recent years. Implicit in this excitement is the notion that physical experiences provide unique value above and beyond what can be offered via digital means, and therefore that combining the two can galvanize sales. However, the specific sources of this marketing potential remain undertheorized and the factors determining the appropriateness of such implementations remain unclear. Based on an extensive review of relevant literatures, we begin by considering a particularly important potential source of phygital marketing’s power. Specifically, we bring together findings from consumer psychology and neuroscience to provide a mechanistic account explaining how the combination of reduced “pain of payment”, facilitated by digital purchasing technologies, and the product attachment generated by real or simulated product experiences prior to purchase holds the potential to increase sales. We then propose a more general theoretical framework grounded on a review of primary and secondary research findings from consumer psychology and consumer neuroscience to explain the potential power of phygital marketing experiences, account for their unique value, and provide a platform for future research. The paper equips both academics and practitioners with a better and more scientific understanding of the practical dimensions of phygital commerce and lays a foundation for future enquiry. Full article

Different and profound are the consequences of the further development of artificial intelligence (AI) on society. One of the manifestations of the upcoming changes is the plethora of novel ways in which companies may organize labor and capital. So far, the influence of AI on organizational structure has been mainly studied from either a technological or a broader decision-making perspective. Our paper provides a unique take on the topic, emphasizing the distinctive role of human agency and its function in the upcoming AI-driven organizational changes. Relying on the existing academic literature, we theorized a set of hypotheses concerning best fits to the AI contingency on both macro and meso-organizational levels. To test whether the hypothesized changes might encounter organizational inertia or resistance from jobholders, multiple correspondence analysis (MCA) was applied to the online survey results. Four types of current and potential jobholders were distinguished according to their explicit attitudes towards hypothesized organizational changes: skeptics, doubtful skeptics, optimists, and doubtful optimists, the latter consisting primarily of emerging adults. Finally, we developed a model of intraorganizational response to the AI contingency based on four theoretical groups of individuals, as determined by the analysis. Our findings showed doubtful optimists to be the most important group, able to set organizational trends and positively influence skeptics and doubtful skeptics. Accordingly, promoters of AI-driven organizational changes are advised to design their communication efforts around emerging adults. As the survey was conducted amid the COVID-19 pandemic, its sociological and managerial implications are relevant to the looming reality of the postpandemic world. Full article

In the era of digitally dominated competition, where the effectiveness of Facebook ads prompts the social media marketing strategy, new opportunities arise for most industries. In this context, this study aims to discover and summarize the key optimisations regarding the creative ad components needed to run highly personalized ads based on a user profile. The participants were Facebook users between the ages of 18 and 65+ who were interested in dental services. Qualitative methods were adopted in order to discover suitable options for professionals to grow their business. In the first stage, the A/B split test using the Facebook Ads manager labelled the most effective creative component. In the second stage, an eye-tracking experiment generated 30 heatmaps that showed the differences between the segments. The results show solutions for attracting users by increasing the level of personalization of the ads. They are more beneficial for social media campaigns aimed at brand awareness targeting women and showing them a happy human face. When the target audience is men, technical details are preferred in order for the ad to become more attractive for them. This study enriches the literature and empowers professionals to deploy social media marketing growth strategies to attract users and make them convert to their full potential. Full article

The COVID-19 health and economic crisis has affected all areas of social life globally, including the economy. The world economy has declined due to purchasing power for individuals who have been forced to stay at home and cannot perform work. These restrictions to prevent the spread of SARS-Cov-2 have led to an increase in electronic commerce and mobile commerce as tools for procuring goods and services. In this paper, we conducted a longitudinal analysis of mobile commerce as an essential electronic commerce component, establishing the main drivers of mobile commerce and the intensity of their influences. The research focuses on mobile commerce in the United States (U.S.). It covers the period 2010–2020, the last year of this period capturing the context of the COVID-19 pandemic and its impact on electronic commerce (e-commerce) and mobile commerce (m-commerce). In the macroeconomic analysis of competitiveness, we established the main drivers of m-commerce, using artificial neural networks and the mediation effects found between the variables that describe m-commerce, e-commerce, and total sales, using structural equation modeling. The research results indicate an increase in the share of e-commerce in total sales and a predominance of the m-commerce share in e-commerce on the background of traffic restrictions and social distance rules imposed due to the COVID-19 pandemic. Stakeholders in the m-commerce area should consider the following enhancing drivers: increasing internet speed, expanding 5G and Wi-Fi networks, and increasing accessibility and trust in mobile devices and applications. Full article

Big Data technologies have significantly increased the possibility for sellers to adopt personalisation strategies, especially in digital markets. Among such strategies, price discrimination, a practice where the same commodity is sold at different prices, either to the same customer or to different customers, stands out. Particularly, the online airline ticket market has risen the attention of economists in recent studies, both because of its specificity and of the high data availability. This manuscript enters the debate and analyses the airline ticket market in an original way. Indeed, the aim of this work is to empirically understand whether some airline companies discriminate in prices by using the customers’ data that they collect from their websites, and, if so, which is the impact on social welfare. For performing this assessment, a software that is able to automatically collect pricing data is developed and freely released. By executing the software in two time periods, tickets prices of three airlines, three itineraries, and four different user profiles are acquired. A double analysis is performed to check if customers’ information are used to discriminate (intra-user), and if different prices are offered to distinct user profiles (inter-user). Moreover, the analyses consider control data collected from the API of the Global Distribution System Amadeus, the main flight booking platform dedicated to travel agents. Upon inspection, no evidence is found in this study to support the hypothesis that airlines use price discrimination techniques. Full article

With the spread of the COVID-19 pandemic and the increasing importance of e-commerce, the study of online consumer behavior is of particular relevance. The purpose of this study was to form a methodological approach to assess the relationships and the level of influence of the factors activating the purchasing behavior of online consumers against the background of the COVID-19 pandemic. The research methodology was based on the transformation of Cattell’s questionnaire and the implementation of correlation analysis. To determine the predisposition of online consumer behavior at the time of making a purchase decision, this study used the questionnaire method. The survey was conducted among online shoppers in the top 10 countries in terms of e-commerce market growth. The scientific contribution is the proposed methodological toolkit to assess the purchasing behavior of online consumers, which identifies the most influential factors in their purchasing behavior and provides an opportunity to assess the dynamics of their activity during the study period, to identify key trends and determine changes in their behavior. The research revealed what changes in online consumer buying behavior are typical in the COVID-19 pandemic. The impact of consumer awareness and experience has increased. Online consumers have become more experienced, which has influenced the activity of their buying behavior. This study proved the shifting influence of online consumer purchasing behavior factors during the pandemic. The increasing importance of the speed of decision making by consumers when purchasing goods and services online was determined. Full article

This study aimed to provide a comprehensive analysis of the factors that determine and shape consumers’ behavioral intention to adopt mobile commerce (m-commerce). By integrating the core constructs from the Unified Theory of Acceptance and Use of Technology (UTAUT), together with the trust-building mechanisms, this study explored the importance of the institutional mechanisms and their moderating effects between trust in the vendors and intention to adopt m-commerce. Traditionally, the effects of institutional mechanisms on trust and adoption intention have been considered separately in different study contexts. The purpose of this study was to extend the literature by simultaneously exploring two institutional mechanisms that are conceptually highly similar to each other, namely, structural assurance (SA) and perceived effectiveness of e-commerce institutional mechanisms (PEEIM). A self-administered survey was used to collect data, which were analyzed using partial least squares structural equation modelling (PLS-SEM). The results revealed that most of the constructs examined have significant relationships with the intention to adopt m-commerce. Additionally, PEEIM exhibits a significant moderating effect but SA does not. This study delineates how trust-building mechanisms play important roles in increasing consumers’ confidence in order to promote m-commerce adoption. Full article

Recent research in cryptocurrencies has considered the effects of the behavior of individuals on the price of cryptocurrencies through actions such as social media usage. However, some celebrities have gone as far as affixing their celebrity to a specific cryptocurrency, becoming a crypto-tastemaker. One such example occurred in April 2021 when Elon Musk claimed via Twitter that “SpaceX is going to put a literal Dogecoin on the literal moon”. He later called himself the “Dogefather” as he announced that he would be hosting Saturday Night Live (SNL) on 8 May 2021. By performing sentiment analysis on relevant tweets during the time he was hosting SNL, evidence is found that negative perceptions of Musk’s performance led to a decline in the price of Dogecoin, which dropped 23.4% during the time Musk was on air. This shows that cryptocurrencies are affected in real time by the behaviors of crypto-tastemakers. Full article

The aim of this paper is to present the use of an innovative approach based on MCDM methods as the main component of a consumer Decision Support System (DSS) by recommending the most suitable products among a given set of alternatives. This system provides a reliable recommendation to the consumer in the form of a compromise ranking constructed from the five MCDM methods: the hybrid approach TOPSIS-COMET, COCOSO, EDAS, MAIRCA, and MABAC. Each of the methods used contributes significantly to the final compromise ranking built with the Copeland strategy. Chosen MCDM methods were combined with the objective CRITIC weighting method, and their performance was presented on the illustrative example of choosing the most suitable mobile phone. A sensitivity analysis involving the $r_w$ and $WS$ correlation coefficients was performed to determine the match between the compromise ranking of the candidates and the rankings provided by each MCDM method. Sensitivity analysis demonstrated that all investigated compromise candidate rankings show high convergence with the rankings provided by the particular MCDM methods. Thus, the performed study proved that the proposed approach shows high potential to be successfully used as a central component of DSS for recommending the most suitable product. Such DSS could be a universal and future-proof solution for e-commerce sites and websites, providing advanced product comparison capabilities in delivering a recommendation to the user as a final ranking of alternatives. Full article

With the rapid development of e-commerce services, online retail has evolved from multi-channel to omni-channel in order to provide customers with more services. However, reverse logistics services (returns and exchanges) have become the target of many fraudulent activities, causing a lot of economic losses for many online retail companies. The current challenge of the traditional countermeasure is it requires a lot of manpower and training resources. In this study, we propose ESPRES, a system that adopts blockchain technology to prevent fraudulent behavior in the process of returns and exchanges with the smart contract and multi-attribute decision-support method to help consumers choose a suitable payment program. A practical implication of this study is that by adopting blockchain technology, a great amount of manpower used on determining whether each return or exchange is fraudulent can be reduced since merchants can check the product ownership. In addition, due to the fact that the footprint of goods cannot be forged, it can also prevent counterfeit or parallel imports of goods. Full article

A series of digital marketing transformations have been carried out at Chinese gas stations. From the perspective of user experience, the article discovers the problems in the digital service system of gas stations. Through semi-structured interviews, we collect consumers’ actual usage of digital equipment and service systems. The research adopts grounded theory to encode qualitative data. The behavioral state and psychological needs of consumers in the driving situation are analyzed. The study clarifies the influence of consumer behavior status, service context process, key task difficulty, and service information visualization on service experience. The discovery of service problems in turn help to further optimize the digital service system. The constructed SITE model clarifies the key factors of user experience in the gas station scenario. The research findings can provide a theoretical reference and practical guidance for gas station business owners, managers, and designers. Full article

The pervasive adoption of mobile devices and proximity technologies enables firms to trace consumers’ trajectories and locations. This connects firms’ marketing and operations strategies more tightly with consumer mobility. In this paper, we propose a novel analytical model to examine the economic effects of consumer mobility on pricing and advertising strategies by incorporating consumers’ Lévy-walking behavior into advertising economics models. We ascertain the convergent effect of consumer mobility, i.e., consumers’ convergence to a firm leads to higher product price and advertising level. Meanwhile, it improves social welfare by increasing firm profit and consumer surplus. More interestingly, we find that consumers’ average movement distance (AMD) has opposing influences in pricing and advertising strategies. Specifically, longer AMD strengthens the convergent effect on advertising strategy but weakens that on pricing strategy. Finally, we also conduct a numerical analysis to uncover the impacts of the presence of proximity technologies on advertising outcomes. The results of this paper provide advisable guidance to firms on how to craft and adjust pricing and advertising strategies in accordance to consumer mobility. Moreover, the results present insights on welfare implications of informative advertising from the perspective of consumer mobility. Full article

The aim of the paper is to determine the influence of BMI based on new technologies on a company’s competitive advantage. In order to accomplish the aim a quantitative research was performed using the computer assisted telephone interview (CATI) method. There are two main outcomes of the research. Firstly, BMI based on new technologies has a positive influence on a company’s competitive advantage. Secondly, it was proven that the greater the use of technologies for BMI the greater a company’s competitive advantage is. Taking into account the research results, the paper explains how they contribute to the development of two theories—the theory of innovation as well the theory of competitive advantage. Several recommendations for business practice as well as policy makers are also formulated. Full article

This paper examines the dynamic competition between platform firms in two-sided markets with network externalities. In our model, two platforms compete with each other via a contest to dominate a certain market. If one platform wins the contest, it can serve the market for a certain duration as a monopolistic platform. Our paper shows that platform firms can compensate for cost disadvantages with network effects. A head start (e.g., technological advantage) does not guarantee future success for platform firms. Network effects and cost efficiency are decisive for future success. Interestingly, higher costs of a platform can induce higher platform profits in our dynamic model. Moreover, we find that a platform’s size and profit are not necessarily positively correlated. Our model also provides new insights with respect to the underlying causes for the emergence of market dominance. The combination of technological carry-over and network effects can explain a long-lasting dominance of a platform that benefits from a head start. The necessary preconditions for this emergence are convex costs, small network effects and high carry-over. Full article

In coherence with the progressive digitalization of all areas of life, the Internet of Things (IoT) is a flourishing concept in both research and practice. Due to the increasing scholarly attention, the literature landscape has become scattered and fragmented. With a focus on the commercial application of the IoT and corresponding research, we employ a co-citation analysis and literature review to structure the field. We find and describe 19 research themes. To consolidate the extant research, we propose a research framework, which is based on a theoretical implementation process of IoT as a concept, specific IoT applications, or architectures integrated in an adapted input–process–output model. The main variables of the model are an initial definition and conceptualization of an IoT concept (input), which goes through an evaluation process (process), before it is implemented and can have an impact in practice (output). The paper contributes to interdisciplinary research relating to a business and management perspective on IoT by providing a holistic overview of predominant research themes and an integrative research framework. Full article

Online sources of information are a matter of special interest in tourism research. In particular, they are key elements in the formation of destination image. The purpose of this paper is to examine the relationship between online sources of information and destination image and to analyze the mediating role of motivation to co-create in that relationship. A research model was developed, and hypotheses were tested on data collected from 394 usable responses about the World Heritage city of Cuenca (Spain). The results show that online commercial sources have a direct positive impact on the conative, affective and cognitive dimensions of the tourist image, in this order. Additionally, this study supports the view that motivation to co-create mediates the relationship between online information sources and destination image. Finally, motivation to co-create was also found to have a positive and direct impact, in this order, on conative, cognitive and affective image. The main value of our research is that it underlines the essential influence of motivation to co-create in the relationship between online information sources and destination image. This study also provides a critical review of the existing literature by positing a conceptual theoretical framework that links three types of online sources of information (social media sources, online commercial sources and online non-commercial sources) and destination image. Full article

Online social networks, as popular media and communications tools with their own extensive uses, play key roles in public opinion polls, politics, economy, and even governance. An important issue regarding these networks is the use of multiple sources of publishing or re-publishing news and propositions that can influence audiences depending on the level of trust in these sources between users. Therefore, estimating the level of trust in social networks between users can predict the extent of social networks’ impact on news and different publication and re-publication sources, and correspondingly provide effective strategies in news dissemination, advertisements, and other diverse contents for trustees. Therefore, trust is introduced and interpreted in the present study. A large portion of interactions in social networks is based on sending and receiving texts employing natural language processing techniques. A Hidden Markov Model (HMM) was designed via an efficient model, namely SenseTrust, to estimate the level of trust between users in social networks. Full article

In today’s world, crowdsourcing is regarded as an effective strategy to deal with a high volume of small issues whose solutions can have their own complexities in systems. Moreover, requesters are currently providing hundreds of thousands of tasks in online job markets and workers need to perform these tasks to earn money. Thus far, various aspects of crowdsourcing including budget management, mechanism design for price management, forcing workers to behave truthfully in bidding prices, or maximized gains of crowdsourcing have been considered in different studies. One of the main existing challenges in crowdsourcing is how to ensure truthful reporting is provided by contributing workers. Since the amount of pay to workers is directly correlated with the number of tasks performed by them over a period of time, it can be predicted that strong incentives encourage them to carry out more tasks by giving untruthful answers (providing the first possible answer without examining it) in order to increase the amount of pay. However, crowdsourcing requesters need to obtain truthful reporting as an output of tasks assigned to workers. In this study, a mechanism was developed whose implementation in crowdsourcing could ensure truthful reporting by workers. The mechanism provided in this study was evaluated as more budget feasible and it was also fairer for requesters and workers due to its well-defined procedure. Full article

Drawing on expectation disconfirmation theory, this study explores the dyadic nature of omni-channel consistency on customer experience. Specifically, we propose a conceptual model that focuses on a brand’s offline channel customer experience relative to that of its online channel, and test the influences of customer experience (in)consistency on customer satisfaction, which then improves repurchase intention and word-of-mouth. The results of polynomial regressions on 265 survey respondents indicate that given omni-channel customer experience inconsistency, customers prefer consistent online and offline experiences. For omni-channel consistency at lower levels of customer experience quality, customers prefer consistency at higher levels of quality. For omni-channel inconsistency where offline customer experience quality is lower than that online, customers prefer omni-channel inconsistency, where offline customer experience quality is higher than that online. These findings produce not only theoretical contributions but also insightful suggestions for how customer experience can be taken into consideration in the promotion of a brand’s omni-channel service success. Full article

The vigorous development of e-commerce has led to online retailers or platforms increasing the capacity of online shopping carts. A large number of products are added to the online shopping cart, but they are not “emptied.” The resulting behavior of products being stuck in the shopping cart is called the “shopping cart abandonment behavior.” Previous literature has focused on the large number of antecedent variables that affect shopping cart abandonment behavior in the pre-decision stage of online shopping. This previous research has studied how to reduce shopping cart abandonment behavior from the perspective of consumers. By focusing on the post-decision-making stage of shopping, this research proposes to sort the products in a chronological order (ascending and descending order) after the products are added to the shopping cart and reduce shopping cart abandonment behavior through the intermediary of forgetfulness and choice overload. We use an exploratory study and two laboratory experiments to reveal the above intermediary mechanism. Our results show that online shopping cart abandonment generally occurs in shopping carts on all major platforms. Forgetting and shopping cart page rendering may be the reasons that lead to shopping cart abandonment behavior. In the case of targeted tasks, ascending order has a significant impact on abandonment behavior, choice overload mediated this effect. Full article

This study examined social media’s role in various levels of research, development, and performance within enterprises in Kuwait. The research incorporated four inductive case analyses in various sectors. The case studies epitomize the supply chain of Kuwaiti enterprises, including small and medium-sized enterprises (SMEs). Media richness theory and social exchange effectuation theory were utilized to create an effective theory and a theoretical framework. This study collected data via a questionnaire completed by 100 managers employed by Kuwaiti SMEs specialized in the food sector and interviews with eight managers. Numerical data were analyzed via SPSS software, while textual data were analyzed by applying thematic analysis. The results of this study suggest that Kuwaiti companies should adopt social media platforms and other novel, innovative outlets to publicize their organizations and maximize performance. Social media richness and openness tend to determine the supplier selection process in most Kuwaiti enterprises, leading to positive transactional and social impacts on entrepreneurship. Full article

Retailers have little control over what their customers say about their products and services online. Review platforms (e.g., Yelp and Travelocity) are rife with negativity, from both real customers with bad experiences and from fake reviews created by competitors. These negative reviews have been shown to influence the purchasing behavior of future consumers. Many platforms do afford companies some control by including them in the online conversation about their products or services. Crafting a response to a poor review which appeals to future consumers may mitigate some of the negative outcomes associated with that review. This study advances our knowledge of responding to negative reviews by adding to the growing body of research, using a simulation-based experiment to test the influence of three elements of a review response on purchase intention (i.e., an apology, an explanation and a pledge to correct the problem identified in the review). In doing so, the data show that purchase intention increases only when a response contains all three elements. Implications for e-commerce researchers and review platform developers are discussed. Full article

The startup business ecosystem in India has experienced exponential growth. The amount of investment in Indian startups in the last decade demonstrates the strong interest of the technology industry to these business models based on innovation. In this context, the present study aims to identify investment opportunities for investors in Indian startups by identifying key indicators that characterize the startup ecosystem in India. To this end, a three steps data mining method is developed using data mining techniques. First, a sentiment analysis (SA), a machine learning approach that classifies the topics into groups expressing feelings, is applied to a dataset. Next, we develop a Latent Dirichlet Allocation (LDA) model, a topic-modeling technique that divides the sample of n = 14.531 tweets from Twitter into topics, using user-generated content (UGC) as data. Finally, in order to identify the characteristics of each topic we apply textual analysis (TA) to identify key indicators. The originality of the present study lies in the methodological process used for data analysis. Our results also contribute to the literature on startups. The results demonstrate that the Indian startup ecosystem is influenced by areas such as fintech, innovation, crowdfunding, hardware, funds, competition, artificial intelligence, augmented reality and electronic commerce. Of note, in view of the exploratory approach of the present study, the results and implications should be taken as descriptive, rather than determining for future investments in the Indian startup ecosystem. Full article