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This study aims to propose a risk-induced game theoretic forecasting model to predict average daily rate (ADR) under COVID-19, using an advanced recurrent neural network.

Using three data sets from upper-midscale hotels in three locations (i.e. urban, interstate and suburb), from January 1, 2018, to August 31, 2020, three long-term, short-term memory (LSTM) models were evaluated against five traditional forecasting models.

The models proposed in this study outperform traditional methods, such that the simplest LSTM model is more accurate than most of the benchmark models in two of the three tested hotels. In particular, the results show that traditional methods are inefficient in hotels with rapid fluctuations of demand and ADR, as observed during the pandemic. In contrast, LSTM models perform more accurately for these hotels.

This study is limited by its use of American data and data from midscale hotels as well as only predicting ADR.

This study produced a reliable, accurate forecasting model considering risk and competitor behavior.

This paper extends the application of game theory principles to ADR forecasting and combines it with the concept of risk for forecasting during uncertain times.

This study is the first study, to the best of the authors’ knowledge, to use actual hotel data from the COVID-19 pandemic to determine an appropriate neural network forecasting method for times of uncertainty. The application of Shapley value and operational risk obtained a game-theoretic property-level model, which fits best.

This study has two major objectives. First, comprehensively review the literature on transparency in supply chain management. Second, based on a critical analysis of literature, identify the attributes and sub-attributes of supply chain transparency and develop a numerical measure to quantify transparency in supply chains.

A systematic literature review (SLR) was conducted using the PRISMA approach. Utilizing SCOPUS database past eighteen-year papers search resulted in 249 papers to understand major developments in the domain of supply chain transparency. Subsequently, graph theoretic approach is applied to quantify transparency in supply chain and the proposed index is evaluated for case supply chains from pharma and dairy sectors.

It can be concluded from SLR that supply chain transparency research has evolved from merely tracking and tracing of the product towards sustainable development of the whole value chain. The research identifies four major attributes and their sub-attributes that influence transparency in supply chains, which are used to develop transparency index. The proposed index for two sectors helps to understand areas that need immediate attention to improve transparency in the case supply chains.

This paper attempts to understand the development of transparency research in supply chain using the PRISMA approach for SLR. In addition, development of mathematical model to quantify supply chain transparency is a novel attempt that would help benchmark best practices in the industry. Further, transparency index would help to understand specific areas that need attention to improve transparency in supply chains.

Because family businesses are highly complex enterprises, researchers need appropriate theoretical and methodological tools to study them. The neoconfigurational perspective and its accompanying method, qualitative comparative analysis, are particularly well suited to phenomena characterized by complex causality, but their uptake in family business research has been slow and fragmented. To remedy this, the authors highlight their unique ability to address research questions for which other approaches are not well suited and discuss how they might be applied to family business phenomena.

The authors introduce the core tenets of the neoconfigurational perspective and how its set-theoretic epistemology differs from traditional approaches to theorizing and analysis. The authors then use a dataset of family firms to present a primer on conducting qualitative comparative analysis and interpreting the results.

The authors find that family firm resources can be combined in multiple ways to affect business survival, suggesting that resources are substitutable and complementary. The authors discuss how the unique features of the neoconfigurational approach, namely equifinality, conjunctural causation and causal asymmetry, can be fruitfully applied to break new ground in scholarly understanding of family businesses.

This article allows family business researchers to apply the neoconfigurational approach without first having to consult multiple and disparate sources often written for other disciplines. This article explicates how to leverage the theoretical and empirical advantages of the neoconfigurational approach in the context of family businesses, supporting a more widespread adoption of the neoconfigurational perspective in family business research.

This study highlights the impact of mental accounts on a user's decision-making regarding payment schemes and aims to determine the pricing strategy for the first-enjoy-after-pay service offered by the two-sided media platforms.

This study establishes a game-theoretic model and utilizes backward induction to derive the equilibrium price by maximizing the monopolist's profit.

The findings indicate that the conditions for a two-sided media platform to offer the first-enjoy-after-pay service depend on the trade-off between pleasure attenuation and pain buffering and the effect of time discounts. Moreover, the authors found that the time discount is a critical factor in determining pricing strategies under various payment schemes offered by the platform.

This work adopts a uniform pricing strategy for users who opt for either immediate or post-payment schemes. Nevertheless, it is important to note that this approach has limitations in terms of offering discriminatory pricing for those who choose both payment schemes.

This analytical work provides valuable insights for two-sided media platforms to optimize their payment scheme strategies and pricing considering the influence of a user's mental account.

In a two-sided media platform, the authors provide applicable conditions for the platform to offer first-enjoy-after-pay service considering the effect of mental accounts. Further, the authors show the optimal pricing strategy under different payment schemes provided by the platform.

This study attempts to discover effective strategies for mobile commerce applications (apps) to grow their consumer base by releasing app strategic updates. Drawing on the landscape search model from strategy research, this study conceptualizes mobile app update strategy as three interdependent decisions, i.e. what business elements are changed in an app strategic update, how substantial the changes are and when strategic updates are released relative to the competitive environment.

Using a field data set of 1,500 strategic updates of seven rival apps in the mobile travel market, this study integrated fuzzy set qualitative comparative analysis (fsQCA) with econometric analysis to analyze how app strategic update decisions interdependently influence app performance.

This study identified three effective and one ineffective mobile app update strategies from the mixed-method analysis, which verified the complex interdependency of app strategic update decisions. A general takeaway from these strategies is that a complex strategy problem on the mobile platform must be solved with respect to the constraints and capabilities of mobile technology.

This study moves beyond a linear view of the relationship between app update frequency and app performance and provides a holistic view of how and why app strategic update decisions mutually influence one another in their impact on app performance. This work makes contributions by identifying interdependency as a conceptual bridge between strategy and mobile app literature and developing an empirically testable version of the landscape search model.

Sales organizations embrace technological innovation. However, salespeople’s willingness to use new technology influences a firm’s return on investment, representing a significant concern for the organization. These concerns highlight tensions regarding the tradeoffs associated with technology implementations. The purpose of this study is to offer insights that help reduce the complexities of sales technology (ST) by exploring the changing dynamics of contemporary business relationships.

This paper synthesizes the ST literature using the service ecosystem perspective to propose the sales techno-ecosystem (STE) framework, providing new insights into organizational decision-making related to the ongoing digital transformation of sales tasks.

This synthesis of the ST literature with the service ecosystem seeks to clarify the impact of technology within the evolving nature of buyer–seller relationships by providing four unique perspectives.

Perspective 1 reviews the sales-service ecosystem framework and develops the theoretical underpinnings and relevant terminologies. Perspective 2 summarizes critical aspects of the ST literature and provides foundations for future research in the STE. Perspective 3 offers a more granular view, explicating roles and contexts prevalent in buyer–seller–technology interactions. Perspective 4 provides a set of tenets and advances research questions related to each tenet.

The culmination of these four perspectives is the introduction of five key tenants designed to help guide strategy and research.

The paper advances Hartmann et al. (2018) service ecosystem paradigm by explicating critical aspects of its ST domain to generate insights for theory and practice.

During the past few years, social media has faced the challenge of maintaining its user base. Reports show that the social media giants such as Facebook and Twitter experienced a decline in their users. Taking WhatsApp's recent change of its terms of use as the case of this study and using the push-pull-mooring model and a configurational perspective, this study aims to identify pathways for switching intentions.

Data were collected from 624 WhatsApp users recruited from Amazon Mechanical Turk and analyzed using fuzzy set qualitative comparative analysis (fsQCA).

The findings identify seven configurations for high switching intentions and four configurations for low intentions to switch. Firm reputation and critical mass increase intention to switch, while low firm reputation and absence of attractive alternatives hinder switching.

This study extends extant literature on social media migration by identifying configurations that result in high and low switching intention among messaging applications.

The study identifies factors the technology service providers should consider to attract new users and retain existing users.

This study complements the extant literature on switching intention that explains the phenomenon based on a net-effect approach by offering an alternative view that focuses on the existence of multiple pathways to social media switching. It further advances the authors’ understanding of the relevant importance of switching factors.

Managing resources is crucial for firms to gain competitive advantages and succeed, particularly for startups with limited resources. It is important to understand how digital startups in general and digital academic spin-offs (ASOs) in particular may orchestrate their resources to optimize value. This paper integrates the resource-based perspective with digital entrepreneurship to analyze the resource configurations leading to success of digital ASOs.

The paper adopts an inductive approach and applies qualitative comparative analysis (QCA) on a longitudinal dataset of digital ASOs to identify the resource configurations for a successful outcome.

The authors' paper identifies two main paths to success among digital ASOs, consisting of five distinct resource configurations. The first path is termed “market exploiters” that operate in favorable market conditions where specific technological resources and research collaboration resources are lacking. The second path involves “technology explorers” that combines both technological and commercial resources to achieve success.

By outlining distinct pathways to the success of digital ASOs, this paper contributes to the digital academic entrepreneurship literature and the resource-based view of entrepreneurial firms. The paper also suggests implications for policymakers and managers in managing resources for the success of digital ventures.

By exploring the resource configurations leading to the success of ASOs commercializing digital technologies, the paper shows that favorable market conditions and complementary resource configurations can be alternative pathways to success.

This study explores the key platform affordances that online social platform providers need to offer digital creators to strengthen the creator ecosystem, one of the leading accelerators for platform growth. Specifically, it aims to investigate how these affordances make the dynamic combinations for high platform quality across diverse platform types and demographic characteristics of digital creators.

This study adopts a multi-method approach. Drawing upon the affordance theory, Study 1 aims to identify the key affordances of online social platforms based on relevant literature and the qualitative interview data collected from 22 digital creators, thereby constructing a conceptual framework of key platform affordances for digital creators. Building on the findings of Study 1, Study 2 explores the dynamic combinations of these platform affordances that contribute to platform quality using a configurational approach. Data from online surveys of 185 digital creators were analyzed using fuzzy set qualitative comparative analysis (fsQCA).

The results of Study 1 identified key online social platform affordances for digital creators, including Storytelling, Socialization, Design, Development, Promotion, and Protection affordance. Study 2 showed that the combinations of these platform affordances for digital creators are diverse according to the types of platforms, creators’ gender, and their professionality.

Like many studies, this research also has several limitations. One limitation of the research is the potential constraint of the extent of how well the data samples represent the group of creators who are actively producing digital content. Despite the addition of screening questions and meticulous data filtering, it is possible that we did not secure sufficient data from creators who are actively engaged in creative activities. In future research, it is worth contemplating the acquisition of data from actual groups of creators, such as creator communities. Future researchers anticipate obtaining more in-depth and accurate data by directly involving and collaborating with creators.

This study highlights the need for online social platforms to enhance features for storytelling, socializing, design, development, promotion, and protection, fostering a robust digital creator ecosystem. It emphasizes clear communication of these affordances, ensuring creators can effectively utilize them. Importantly, platforms should adapt these features to accommodate diverse creator profiles, considering differences in gender and expertise levels, especially in emerging spaces like the Metaverse. This approach ensures an equitable and enriching experience for all users and creators, underlining the importance of dynamic interaction and inclusivity in platform development and creator support strategies.

This study underscores the social implications of evolving digital creator ecosystems on online platforms. Identifying six key affordances essential for digital creators highlights the need for platforms to enhance storytelling, socializing, design, development, promotion, and product protection. Crucially, it emphasizes inclusivity, urging platforms to consider diverse creator profiles, including gender and expertise differences, particularly in transitioning from traditional social media to the Metaverse. This approach nurtures a more robust creator ecosystem and fosters an equitable and enriching experience for all users. It signals a shift towards more dynamic, adaptive online environments catering to diverse creators and audiences.

For academics, this study builds the conceptual framework of online social platform affordances for digital creators. Using the configurational approach, this study identified various interdependent relationships among the affordances, which are nuanced by specific contexts, and suggested novel insights for future studies. For practices, the findings specified by creators and platform types are expected to guide platform providers in developing strategies to support digital creators and contribute to platform growth.

The role of chief executive officer (CEO) personal characteristics in shaping corporate policies has attracted increasing academic attention in the past two decades. In this review, the authors synthesize extant research on CEO attributes by reviewing 232 articles published in 29 journals from the accounting, finance and management literature. This review provides an overview of existing findings, highlights current trends and interdisciplinary differences in research approaches and identifies potential avenues for future research.

To review the literature on CEO attributes, the authors manually collected peer-reviewed articles in accounting, finance and management journals from 2000 to 2021. The authors conducted in-depth analysis of each paper and manually recorded the theories, data sources, country of study, study period, measures of CEO attributes and dependent variables. This procedure helped the authors group the selected articles into themes and sub-themes. The authors compared the findings in various disciplines and provided direction for future research.

The authors highlight the role of CEO personal attributes in influencing corporate decision-making and firm outcomes. The authors categorize studies of CEO traits into three main research themes: (1) demographic attributes and experience (including age, gender, culture, experience, education); (2) CEO interactions with others (social and political networks) and (3) underlying attributes (including personality, values and ideology). The evidence shows that CEO characteristics significantly affect a wide range of specific corporate policies that serve as mechanisms through which individual CEOs determine firm success and performance.

CEO selection is one of the most crucial decisions made by corporations. The study findings provide valuable insights to corporate executives, boards, investors and practitioners into how CEOs’ personal characteristics can impact future firm decisions and outcomes that can, in turn, inform the high-stake process of CEO recruitment and selection. The study findings have significant practical implications for corporations, such as contributing to executive training programs, to assist executives and directors attain a greater level of self-awareness.

Building on the theoretical foundation of upper echelons theory, the authors offer an integrated theoretical framework to consolidate existing empirical research on the impacts of CEO personal attributes on firm outcomes across accounting and finance (A&F) and management literature. The study findings provide a roadmap for scholars to bridge the interdisciplinary divide between A&F and management research. The authors advocate a more holistic and multifaceted approach to examining CEOs, each of whom embodies a myriad of personal characteristics that comprise their unique identity. The study findings encourage future researchers to expand the investigation of the boundary conditions that magnify or moderate the impacts of CEO idiosyncrasies.