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This study explores the factors that influence platform-to-platform cooperation (PPC) and designs a theoretical framework for platform research.

This multi-case study includes a combination of exploratory and explanatory case studies.

From the internal factor perspective, channel integration capability, technology-based order matching capability and service innovation capability positively affects the PPC. From the perspective of external factors, the impact of a new platform entry on the PPC depends on market power and complementarities between platforms in the supply and value chains. Diversity of demand also has a positive effect on the PPC, which is moderated by network externalities. It is worth noting that the incumbent platform prefers to diversify its services for collaborating platforms with a higher level of cooperation. In addition, the higher diversity of demand, the stronger the service innovation capability, which indirectly impacts cooperation positively.

The PPC has gained immense popularity in recent years. However, no scholars have investigated the factors influencing the PPC decisions, which warrants further exploration. This study sheds light on the factors and mechanisms that influence the PPC from both internal and external perspectives.

In developing nations, the utility and intention to use algorithmic trading (AT) platforms and financial services are predominantly reliant on investors’ technological knowledge. This study aims to investigate the effect of investor awareness of AT (AAT), trust in AT (TAT) and acceptance of innovativeness (AOI) on intention to use the AT (IUAT) platforms among Indian investors.

The authors used a structured questionnaire with a five-point Likert scale to collect the data from 392 Indian retail investors through a purposeful sampling approach. And, the authors carried out structural equation modelling to analyse the serial mediation among the latent (independent) and observed (dependent) variables.

The findings suggest that investor awareness exerts a statistically significant and positive effect on the IUAT platforms. Additionally, TAT platforms and innovation acceptance, independently as well as mediator, significantly influences the usage decision of AT platforms among Indian investors.

The findings on determinants of AT platform usage can guide investment regulators to promote technological awareness, build trust and provide a safe algorithmic trading environment for retail investors in India. The suggestions may take the edge off a few behavioural impediments among the investors w.r.t. AT platform usage.

Off the back of extensive literary exploration our field research is among the first that probes an intellectual discourse and documents the empirical evidence on linkages between investor AAT, TAT, AOI and the IUAT platforms in the Indian stock market.

The proliferation of industry platforms has disrupted several industries. Firms adopting a platform business model have experienced a substantial expansion in size and scale, positioning themselves as the foremost valuable entities in market capitalization. Over the past two decades, there has been a substantial expansion in the body of literature dedicated to platforms, and different streams of research have emerged. Despite considerable efforts and the significant progress made in recent years toward a comprehensive understanding of industry platforms, there is still room for further harnessing the field’s diversity. As a result, the aim of this article is to examine the field’s structure, identify research concerns and provide suggestions for future research, thereby enhancing the overall understanding of industry platforms.

We conducted a thorough examination of 458 articles on the topic using bibliometric methods and systematic review techniques.

Through co-citation analysis, we identified five distinct clusters rooted in various bodies of literature: two-sided markets, industry platforms, digital platforms, innovation platforms and two-sided networks. Furthermore, the examination of these five clusters has revealed three key areas that demand further consideration: (1) terminologies, (2) classifications and (3) perspectives.

While previous reviews have provided valuable insights into the topic of industry platforms, none have explored the structure of the field so far. Consequently, as a first step toward advancing the field, we uncover the structure of the literature, identifying three major areas of concern. By addressing these concerns, our goal is to converge different clusters, thereby harnessing the diversity in the field and enhancing the overall understanding of industry platforms.

The purpose of this study is to propose and test an integrated model to explain how trust is built in sharing economy (SE) transactions.

Initially, prior literature was systematically selected and synthesized to develop a comprehensive framework applicable to multiple trust-building perspectives and categories of SE platforms. Then, a survey was conducted to validate the constructs and test the model with Airbnb guests. A sample of 351 responses was collected and analyzed using structural equation modeling.

The results indicate that the cues an individual assesses to infer their counterpart’s trustworthiness and the reasons the individual has for engaging in the SE transaction can explain a large variance in their trust in the counterpart. In addition, the individual’s propensity to trust moderates this relationship.

The proposed model can help identify the most effective trust-building mechanisms. It can be taken as a common knowledge base for scholars to compare the four trust-building perspectives and different categories of SE platforms, as well as to investigate the subject over time and across cultures.

This research can also help practitioners understand the complexity of building trust and design platform features to do so.

A unified model clarifies trust in the SE, aiding platform growth and community bonding. This insight guides platforms in feature enhancement and policymakers in drafting balanced regulations.

To the best of the authors’ knowledge, for the first time, there is a comprehensive and parsimonious model applicable to the four trust-building perspectives and different categories of SE platforms.

This paper aims to explore the promotion decisions of heterogeneous sellers on a decentralized platform under competitive conditions and analyze how seller behaviors impact platform profit, seller revenue, buyer surplus and social welfare.

This paper considers a Cournot model consisting of a platform charging a commission rate and two sellers with different conversion rates and browsing costs. Promotion efforts by sellers can increase traffic, but they also incur promotion costs for sellers. The sellers decide on promotion effort by weighing these two effects. The authors also explore the equilibrium when the platform charges a fixed usage fee.

The seller’s profit improves as its conversion rate increases and worsens as browsing costs increase. Also, increasing the commission rate charged by the platform makes the seller invest less in promotional efforts. Therefore, the platform must consider this trade-off to determine an optimal rate. The analysis shows that the seller with a high conversion rate and high browsing cost plays a greater role in generating more overall revenue. When the market favors such a seller, the platform tends to charge less in order not to impair its profitability.

This paper incorporates conversion rate, buyer’s browsing cost, unit promotion cost and the fee charged by the platform into the model to study sellers’ promotion decisions on decentralized platforms.

In online exchange platforms' sponsored search advertising, the array of product quality signals within a keyword search results list plays a crucial role in shaping buyers' purchasing decisions. This research seeks to explore the impact of various quality signals – namely, ranking position, seller reputation and product price – on ad clicks. Additionally, it examines the role of keyword attributes, such as specificity and popularity, in modulating the effects of these quality signals on advertising clicks.

A total of 5,763 effective data points were collected from a leading B2B electronic platform company, and we employed negative binomial regression with Heckman correction methods to test the hypotheses.

The results indicate that in online exchange platforms, search ad clicks are significantly and positively affected by displayed signals such as ranking position, seller reputation and product price information. Notably, a U-shaped relationship emerges between product price and ad clicks. Furthermore, keyword specificity and popularity distinctly moderate the impact of these displayed signals on ad clicks within online exchange platforms.

This paper addresses the gap in existing research on search advertising by methodically analyzing the impact of various signals displayed in search results and how keyword attributes moderate ad clicks, all through a signaling theory lens.

This study aimed to (1) elucidate the results of a social outcomes assessment and socio-spatial return analysis of a social innovation village (SIV) program in Thailand, (2) develop a social return on investment (SROI) tool for a digital learning platform of cultural heritage and (3) propose the application of an SROI calculator for policy decision-making.

SROI methodology was applied to analyze data from a sample of 110 individuals from the SIV in the Tha Ruea community, Nakhon Phanom province, Thailand, which is renowned for musical instrument making, to assess the social innovation objectives.

Improvement in the grassroots economy led to increased income, translating to assessment outcomes and social values within the tourism community. Social and digital media platforms link physical and digital spaces to facilitate interactive learning and online tourism in the community.

Since the COVID-19 pandemic led to a pronounced economic decline, especially in the tourism sector, the results only partially capture the actual benefits of SROI. To address the challenge of adapting the ecosystem of local tourism into the alternative market, training programs are recommended, including upskilling and new-skilling courses offered by state agencies, to support this technological trend.

This research illustrates how an integrative platform between digital technology and cultural heritage can address the significant shift in tourism behavior and promote a new era of cultural heritage tourism in virtual and physical spaces.

The growth of the internet, access to technology and rapid digital transformations have paved the way for developing attack surfaces for individuals and organizations. There is a dire need to provide cybersecurity awareness most effectively. Gamification-based platforms have evolved to make cybersecurity education more engaging and effective. This study explores the gamification platforms available for cybersecurity training and awareness, the extent to which they are used and their benefits and challenges.

PRISMA 2020 was used to conduct the systematic literature review.

The study comprehends the game design elements and their role in the effectiveness of cybersecurity training and awareness. The study unveils that traditional education methodologies are insignificant in cybersecurity awareness, and gamification-based platforms are more beneficial. The paper summarizes the implications of the findings and further postulates future research directions.

This work comprehends the various forms of gamification platforms and frameworks available for cybersecurity training and will motivate further development of gamification platforms. This paper will help academia, private and public organizations and game designers enhance their gamification-based cybersecurity education interventions.

Zakat has succeeded in becoming one of the safety nets for welfare during the crisis. As a result, continuous improvement is a necessity, especially through strengthening technology adaptation. This study aims to explore the factors determining Muslim behavior on their intention to pay zakat by taking into consideration the adoption of digital technology using the modified Unified Theory of Acceptance and Use of Technology (UTAUT).

The data collected were 265 respondents who live in urban and suburban areas. They were processed using the partial least square structural equation modeling (PLS-SEM) design. Furthermore, the multigroup analysis (MGA) was conducted to capture the difference results between urban and suburban.

The findings show that performance expectancy, social influence, facilitating conditions, perceived security and privacy and zakat literacy significantly increase the intention of Muzakki to adopt financial technology. Perceived security and privacy has succeeded in being an important predictor of digital payment adoption for Muzakki. This paper provides a specific description of the adoption of Muzakki living in urban and suburban areas by using MGA. The research findings illustrate that there is a different urgency between the related variables. Suburban communities have more significant results regarding the research model used.

This research provides new component variables that can drive individuals’ intentions to use digital services to pay zakat online by using the redesigned UTAUT model. Further research can explore more variables related to zakat digitalization, such as social media interaction, by conducting in-depth interviews with stakeholders to improve zakat performance in this digital era.

The result of this research recommends that zakat institutions enhance their zakat literacy and education among the Muslim population to improve zakat performance. The government should pay attention to the digital ecosystem to attract the community to use a digital platform.

This research modified the UTAUT model by integrating several other important constructs to produce more comprehensive findings in investigating the factors that can influence an individual's intention to pay zakat through an online digital platform. This study also examined the indirect effect to obtain significant results by positioning perceived security and privacy as an intervening variable. The implementation of the MGA was conducted to divide research respondents into two categories (urban and suburban) and compare the test results.

The objective of this research conducted in the city of Cuenca is to elaborate on the management platform model of the smart tourist destination (STD). The chapter provides the components to develop such a system as a pilot plan. To maximize the impact of the proposed approach and enhance the decision-making capacities of local actors, the metrics that the Inter-American Development Bank (IDB) developed for the so-called intermediate cities in the study “Cuenca Sustainable City” are used. The platform (www.smarturcuenca.com) considers the transcendence of the current reality of the tourism sector, which is open to multidisciplinary work with other sectors to promote the rational use of cultural and natural resources through the Internet of Things (IoT).