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This paper aims to prove the following hypothesis Problem Statement: HYPOTHESIS (1) User Experience collection of mobile applications can be done using the Crowdsourcing mechanism; (2) User Experience collection of mobile applications are influenced by the mindset of Crowdmembers, culture/ethnicity/social background, ease of interface use and rewards, among other factors.

The authors of this paper, did a literature review first to find if Crowdsourcing was applicable and a used method to solve problems in Software Engineering. This helped us to narrow down the application of Crowdsourcing to the Requirements Engineering-Usability (User Experience) collection. User experience collection of two Malayalam language-based mobile applications, AarogyaSetu and BevQ was done as the next step. Incorporating findings from Study I, another study using AarogyaSetu and Manglish was launched as Study II. The results from both cases were consolidated and analyzed. Significant concerns relating to expectations of Crowd members with User Experience collection were unraveled and the purpose of Study was accomplished.

(1) Crowdsourcing is and can be used in Software Engineering activities. (2) Crowd members have expectations (motivating factors) of User Interface and other elements that enable them to be an effective contributor. (3) An individual’s environment and mindset (character) are influential in him becoming a contributor in Crowdsourcing. (4) Culture and social practices of a region strongly affects the crowd-participating decision of an individual.

This is purely self-done work. The value of this research work is two-fold. Crowdsourcing is endorsed significant in Software Engineering tasks, especially in User Experience collection of mobile applications. Two, the Crowd service requesters can be careful about designing the questionnaire for Crowdsourcing. They have to be aware and prepared to meet the expectations of the Crowd. This can ensure the active participation of potential contributors. Future researchers can use the results of this work to base their research on similar purposes.

This paper aims to explore the impact of metaverse technology on the hospitality and tourism industry. The introduction of metaverse technology has revolutionised the way the hospitality and tourism industry works. In the present study, the authors have investigated the role of social media marketing in the adoption of metaverse technology in hotel booking in India.

An extended technology acceptance model was proposed for an empirical investigation in the Indian context. Sample of 344 respondents was collected across India using a purposive sampling technique for the purpose of data analysis. The structural model analysis is used to analyse the data collected from the respondents using the SmartPLS software to check the structural and the measurement fit of the model.

The adoption intentions were largely influenced by the utility, attitude (ATT) and ease of use of the technology, and social media marketing plays a major role in influencing the perceived usefulness (PU) and ease of use (PEU). The study finds positive ATTs of the customers for using metaverse technology for booking their hotels. PU and PEU significantly influence the ATT of the consumer indicating the traveller’s perception of the usefulness and ease of metaverse technology influence their ATTs towards adoption.

Influence of metaverse technology is at a nascent stage in India specifically for hotel booking and tourism. The authors have used discriminant validity by using the criteria for both the square root of the average variance extracted and heterotrait–monotrait ratio tests, and the results suggest that the constructs in the research are distinct from other.

This study has two main objectives. First, to examine the indirect effects of digital platform capability and digital resilience on digital transformation (DT) outcomes for small- and medium-sized enterprises (SMEs), and second, to investigate how digital business model maturity influences these indirect effects.

The study adopts a quantitative design and collects data through a self-reporting survey from individuals in the technological industries. The Partial Least Squares-Structural Equation Modelling (PLS-SEM) and PLS multi-group analysis examine the measurement and structural models and the significance of differences in indirect paths based on the digital business model maturity level, serving as a moderator.

The findings of this study provide valuable insights into the internationalisation of digital SMEs. They indicate that digital platform capability and resilience fully mediate, connecting digital resources to SME growth. The study also confirms the digital business model maturity’s positive and significant moderating effect on these indirect relationships.

This research contributes to the existing literature by focusing on the international outcomes of platform ecosystems in developing markets. It explores how digital platform capability and resilience support the digital transformation of SMEs, considering their vulnerability due to their small size. The study also fills a research gap by investigating the relationship between big data, digital leadership and the international growth of digital platforms. Lastly, it explores the role of digital maturity in the relationships between antecedents, determinants and outcomes of digitalisation.

The study examines the influence of various congruity factors (economic, safety and Health, hedonic, and functional) on tourists' satisfaction with sharing economy-based services.

A single cross-sectional design is used in the study, with 513 travellers surveyed directly at three different tourist destinations in India. The partial least squares-structural equation modelling approach is used to analyse the data.

The research shows that congruity factors significantly influence tourists' satisfaction with sharing economy-based services. Moreover, satisfaction is strongly associated with recommendation intention for these services and customer loyalty. Additionally, the intention to recommend directly leads to increased customer loyalty.

The results offer pertinent insights for stakeholders in the sharing economy, including tourism marketers, policymakers and corporations. Aligning services with the identified congruity factors can enhance user satisfaction, boost recommendation rates and foster long-standing customer loyalty.

This study stands out for its thorough investigation into how congruity factors influence tourist satisfaction within the context of the sharing economy. Additionally, by focusing on specific demographic differentiators, such as age (gen Z or old gen) and gender (male or female), the study provides a nuanced understanding that enriches the existing body of knowledge.

Consumer behavior has evolved because of technological development. Nowadays, consumers carry out the different stages of the decision-making process by combining multiple devices which has been defined as multi, cross and omnichannel behavior. These behaviors have attracted the attention of academics and become a hot topic in literature. As a result, vast amounts of studies on the subject need to be revised and clarified. Thus, the aim of this chapter is to synthetize the primary academic literature that analyzes multi, cross and omnichannel behavior from the consumer point of view. To do that, first, the main concepts (multi, cross and omnichannel) and their differences are clarified. Second, the major findings of channel mix literature regarding the topics, channel scope and theories are exposed and described. Third, the opportunities and future lines of research are presented. This chapter contributes to the literature by clarifying the conceptualization of multi, cross and omnichannel behaviors; offering a complete picture of the main topics, channel approaches and theories addressed in channel mix literature; and presenting future research opportunities and open research questions in a channel mix context that could serve as a starting point to build further research.

Drawing upon information processing theory (IPT) and natural resource-based view (NRBV), this study analyses the role of social media technologies (SMT) on internal and external environmental collaboration and green innovation (green product, process and managerial innovation).

This study took in-depth empirical research by developing a survey questionnaire to identify the relationship between SMTs, environmental collaboration and green innovation. The respondents of the questionnaire were supply chain professionals working in the manufacturing industry of Pakistan. The survey collected 475 responses, which were tested through PLS-SEM using Smart-PLS.

The study results indicate that SMTs positively influence both internal and external environmental collaboration. Furthermore, internal environmental collaboration (IEC) fosters green products and green managerial innovation. In contrast, external environmental collaboration (EEC) fosters green processes and green managerial innovation. This study has also tested the mediation of IEC and EEC, which shows that both IEC and EEC mediate all the relationships except green process and green product innovation. The results also revealed that innovation capabilities moderate the relationship between environmental collaboration and green innovation.

Though this study has various practical implications, it is not free of limitations. First, the data were collected from Pakistan, and the results may only be compared with other developing countries. Second, few social media platforms have been considered, but they are increasing in numbers and could be used in upcoming studies. Third, green innovation in the context of products, processes and management is considered, but the concept is evolving, and its other indicators can be taken in upcoming studies.

This study addresses the implication of SMTs, environmental collaboration, innovation capabilities and green innovation, which are helpful for managers and policymakers to design policies.

This study provides the seminal operationalization of SMTs in environmental collaboration and green innovation. This study emphasizes innovation capabilities that firms should adopt.

The main aim of this research is to portray how augmented reality (AR) characteristics (augmentation, interactivity, personalization, spatial presence, novelty, entertainment and informativeness) can enhance online customer experience (OCE).

This study conceptualizes a new framework that proposes various relationships between AR characteristics and OCE.

This study is extending the relationships between AR and OCE by including various AR characteristics that have not been tackled by the previous research.

This research provides an original framework on the relationship between AR characteristics and OCE through highlighting the role of media richness theory. The study is considered the first of its kind to combine these AR characteristics and customer experience in a comprehensive framework.

Showrooming presents a complex and evolving challenge to retail managers, as it signifies the emergence of new forms of exchange rules. The purpose of this research is to investigate how factors responsible for information search and evaluation affect showrooming and also consider the consumer mindset as a moderator.

This research undertakes three experimental designs to investigate how the push (i.e. assortment size), pull (i.e. price discount), and mooring (i.e. sunk cost) factors influence consumers' showrooming intention. Specifically, consumers' maximizing tendency plays the role of moderator.

The results reveal that push, pull, and mooring factors are significantly related to consumers' showrooming intention. Furthermore, the findings show that maximizers have higher showrooming intention than satisficers in the context of the push, pull, and mooring factors.

By integrating the push-pull-mooring framework and the maximizing mindset theory, this research proposes a novel research model and the empirical testing results support six hypotheses. The findings add to the body of knowledge in showrooming behavior by taking consumer mindset into account. The results also provide implications for practitioners to develop their retail strategies.

To examine the development of research into the relationship between business process outsourcing (BPO) and innovation, a bibliometric methodology utilizing quantitative analytical methodologies was used. With the aid of a visualization analysis of scientific publications, this study also assessed the state of BPO and innovation practices.

Using the Web of Science database, articles on BPO and innovation that published between 1992 and 2022 were retrieved. Records that had been extracted were examined in terms of publication year, nation, journal, subject area, authors and affiliations with organizations. The research on acupuncture for pain relief was visualized using the VOSviewer application.

An analysis of 219 original and review papers found that during the past 30 years, the overall number of publications has fluctuated constantly. The London University, the Copenhagen Business School and the London School of Economics were the institutions that produced the most articles in this topic. The three main categories of research that emerged from a network analysis based on the co-occurrence of keywords are innovation, outsourcing and performance.

A BP-innovation model must be created, and BPO must go beyond operational duties to incorporate management-wide shared strategic decisions in order to ensure improved performance of the firms. BPO enables a company's management to share knowledge and expertise about the strategic difficulties of outsourcing. A variety of technological and non-technological resources must also be considered when integrating an information technology (IT) infrastructure into BPO decisions in order to achieve greater performance.

Validity of the paper can be justified by it contribution to the existing knowledge. First, linking BPO and innovation – by integrating the arguments of various academics, the study unifies the disparate components and contentious discussions in the relationship between BPO and innovation. Second, this study highlights a research trend, significant studies, relevant terms and concepts in the real world. Third, the study provides future researchers with a tip for statistically analyzing BPO, particularly in light of innovation.

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.