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The paper aims is to see why social conflict caused by class segregation did not occur in Gading Serpong? What factors prevent conflict from occurring? This research seeks to find the causes of the nonoccurrence of social conflict due to class segregation in the Gading Serpong cluster area and explore the factors that restrain conflict there.

This research is qualitative research with data collection techniques through in-depth interviews with several parties identified as brokerages in the research object area. In this context, one of the media and analytical tools is to recognize agents or brokers who connect two groups of people. Brokerage occurs in sectors, patterns or forms of informal, personal relationships; to understand it, one must pay close attention to micro-level relationships and social psychological processes. However, brokerage can have a significant impact on macro-level social relations, as it is generally associated with social integration processes.

The lack of involvement of developers in overcoming social conflicts that occur between Gading Serpong natives and migrants in Gading Serpong housing has given rise to new actors. These new actors are what we can call brokers, where they have a role as brokers who are able to connect between migrants and natives in the Gading Serpong area. The broker phenomenon is actually familiar in academia, where in practice the broker acts as someone who is able to find solutions to problems. The broker is the reason even social segregation is created between migrant citizens and native citizens in Gading Serpong but never becomes a conflict between them.

Even if the brokerage phenomenon is the reason why there is no conflict over social segregation brokerage is not the only factor in this nonconflict segregation. Therefore, to cover the larger area of these suburban segregation problems, there must be further research on this topic.

The practical implication of this research is to encourage the housing developers that create urban housing, such as clusters or other gated communities, to evaluate the social factors, such as potential segregation and conflict management. Also to encourage the developers to get involved and create some social engineering systems, like brokerage, market and other social agents, to create some nonconflict segregation or even more inclusive communities.

This research is uncovering the main reason why social segregation between migrant and native people in Gading Serpong, which could potentially lead to conflict, is never a conflict. The main reason is social actors like brokerage.

Sports tourism was strongly affected by the COVID-19 pandemic, but there is no consensus on what sports tourism should look like in the post-pandemic period. This study explores the future of sports tourism in light of the COVID-19 pandemic and provides an alternative paradigm model.

Data were collected by interviewing sports tourism experts. Data analysis was based on the continuous comparison method during three stages of open, axial and selective coding.

The findings point to the complexity of the future sports tourism industry. Post-COVID-19 sports tourism strongly depends on environmental forces and targeted support, with strategies focused on tourists’ safety and security, digitalization of the industry, and new employment opportunities.

This study contributes to the body of knowledge on sports tourism by providing answers to the current challenges, threats and opportunities associated with the pandemic. The proposed paradigm model could be a guideline for sports tourism practitioners and policymakers to accelerate recovery from COVID-19 in a sustainable and resilient manner.

The business landscapes in Asia and Africa are predominantly characterized by small and medium enterprises (SMEs) facing significant resource constraints. Understanding the capability dynamics of these enterprises in such contexts carries significant implications for theory and practice. This paper aims to addresses a crucial question of whether increasing customer involvement capability consistently yields the necessary rent for enterprises operating under resource constraints in emerging markets in Asia and Africa. By investigating this question, the paper offers SMEs a more nuanced approach to capability development, enabling them to achieve better returns on their investments.

To ensure the robustness of the findings, data were collected from SME service firms operating in two emerging economies: India (Asia) and Ghana (Africa). Data were collected in two waves to allow for catering to specific environmental conditions not accounted for in the study. Two-stage data analysis was then conducted to test the hypothesized relationships across the two countries.

The findings reveal that customer involvement capability does not always lead to an increase in firm-level competitiveness, and the effect follows an inverted U-shaped pattern. However, the nature of this relationship varies under different market conditions in both contexts. Specifically, in periods of low customer demand and intense competition, the relationship is linear and positive. On the other hand, in periods of high demand and competition, the relationship becomes inverted U-shaped, returning to a direct relationship with firm-level competitiveness.

This paper provides a resolution to the critical issue of whether customer involvement capability consistently delivers firm performance benefits, particularly for resource-constrained SMEs in emerging markets. By explaining how SMEs in emerging markets can fully capitalize on their capability development to optimize their resources, this paper makes a distinctive contribution. Moreover, it sheds light on the importance of aligning involvement capabilities with prevailing market conditions for SMEs to reap the maximum benefits.

This study aims to examine how external and internal conditions drive the impact of circular economy mechanism by decomposing into three policy networks in terms of reduce, reuse and recycle, to better understand the contingency model of climate change and effect of firm size on subsequent performance.

Drawing on circular economy network and resource-based view (RBV)-network-resilience strategy framework, a pooled longitudinal cross-sectional data model is developed using a sample of 4,050 Taiwanese manufacturing multinational corporations (MNCs) making foreign direct investment between 2013 and 2018. Structural equation modeling analysis is used to comprehensively examine and investigate each circular economy policy network in the context of climate change and firm size. Post hoc multigroup analysis (MGA) is also conducted.

MGA shows that the reduce policy network is positively and negatively related to manufacturing know-how and production size, respectively. The impact of reuse policy network can enhance the competence of large firms. The recycle policy network is more prominent in terms of competence enhancement of climate change.

MNCs are seeking to build circular economy policy networks to a greater extent, given climate change pressure and guidelines.

This study adds to the circular economy and RBV-network-related literature on climate change and interactions to enhance performance, echoing the recent call on the sustainability of the circular economy of MNCs.

This paper aims to identify, examine, and present an empirical research design of behavioral finance of potential investors during Covid-19.

A well-structured questionnaire was designed; a survey was conducted among potential investors using convenience sampling, and 200 valid responses were collected. The research work uses multiple regression and discriminant function analysis to evaluate the influence of cognitive factors on the financial decision-making of investors.

Recency and familiarity bias are proven to have the highest significant impact on the financial decisions of investors followed by confirmation bias. Overconfidence bias had a negligible effect on the decision-making process of the respondents and found insignificant.

Covid-19 is a temporary phase that may lead to changes in financial behavior and investors’ decisions in the near future.

The paper will help academicians, scholars, analysts, practitioners, policymakers and firms dealing with capital markets to execute their job responsibilities with respect to the cognitive bias in terms of taking financial decisions.

The present investigation attempts to fill the gap in the literature on the intended topic because it is evident from literature on the chosen subject that no study has been undertaken to evaluate the impact of cognitive biases on financial behavior of investors during Covid-19.

The aim of the study was to analyze the performance of Black-Litterman (BL) portfolios using a views estimation procedure that simulates investor forecasts based on technical analysis.

Ibovespa, S&P500, Bitcoin and interbank deposit rate (IDR) indexes were respectively considered proxies for the national, international, cryptocurrency and fixed income stock markets. Forecasts were made out of the sample aiming at incorporating them in the BL model, using several portfolio weighting methods from June 13, 2013 to August 30, 2022.

The Sharpe, Treynor and Omega ratios point out that the proposed model, considering only variable return assets, generates portfolios with performances superior to their traditionally calculated counterparts, with emphasis on the risk parity portfolio. Nonetheless, the inclusion of the IDR leads to performance losses, especially in scenarios with lower risk tolerance. And finally, given the impact of turnover, the naive portfolio was also detected as a viable alternative.

The results obtained can contribute to improve investors practices, specifically by validating both the performance improvement – when including foreign assets and cryptocurrencies –, and the application of the BL model for asset pricing.

The main contributions of the study are: performance analysis incorporating cryptocurrencies and international assets in an uncertain recent period; the use of a methodology to compute the views simulating the behavior of managers using technical analysis; and comparing the performance of portfolio management strategies based on the BL model, taking into account different levels of risk and uncertainty.

Technological innovations provide huge opportunities to expand and revolutionize the scope of products and services offered. This is particularly true for tourism, which is undergoing significant changes due to the development of new technologies. The level of technology diffusion depends on several factors like the exchange of information among peers, and the attitude and shared perception among the contributors. The aim of the study is to explore the diffusion of technology in tourism with a specific focus on the social media discourse around new technologies. Thus, the paper investigates the level of interest in these new technologies analysing the information exchange occurring between individuals on Twitter in order to explore the influence of reciprocal networking.

To capture the attitudes expressed in the industry, the study analyses the ongoing discourse on Twitter as a proxy for the participants “interest in new technologies. Through a social network analysis of the tweets and retweets conducted over a period of nine months, the research maps the level of information exchange about the diffusion of new technologies. Moreover, the sentiment analysis provides an interesting overview of the individuals” attitudes towards the awareness or the adoption of new technologies.

Our analysis has provided several insights: (1) the information network on blockchain in tourism consists of participants who change very quickly over time (high turnover of accounts); (2) some contributors have an extremely important role in influencing the flow of information in the system (information centralization), they can have a generalist (discussing several topics) or a specialist (focusing on a specific topic) behaviour and this strategic choice influences their network's structure; (3) these central nodes also have an impact on the definition of positive and negative sentiment towards a topic (sentiment influencer).

The paper contributes to the literature on technology diffusion, by focusing on one of the preconditions of diffusion that is the shared positive attitude towards technological innovation. More specifically, we adopt a network-based approach, which is useful to explain the level of information exchange and the public discourse that can impact the shared perception and attitude towards technological innovation. The study also highlights the role of knowledge brokers in influencing this public discourse. Future studies can deepen the association between positive perception, higher levels of information exchange and increasing usage of specific technologies. Our results also suggest further exploring the opportunity to combine social media data and other sources of information to shed more light on the technological innovation diffusion processes.

This paper shows how practitioners can benefit from the analysis of information exchange about new technologies in tourism adopting a network perspective with the aim of understanding the level of influence among contributors. Moreover, the increasing interest in blockchain technology and the potential combination between social media data and other sources of information can offer promising insights.

The present study explores the level of technology diffusion through the analysis of information exchange on social media (Twitter). Furthermore, the dynamics of individual user behaviour offers a better understanding about media effects.

While previous research is focused on the users' perception towards the development of new technologies in tourism, the aim of this study is to investigate the dynamics behind the level of diffusion of information and awareness about these new technologies, which still represents an unexplored area of research.

This study aims to analyze the efficient market hypothesis (EMH) of cryptocurrencies on multiple platforms by observing whether there is a discrepancy in the levels of efficiency between different exchanges. Additionally, EMH is tested in a multivariate way: whether the prices of the same cryptocurrencies traded on different exchanges are temporally related to each other. ADF and KPSS tests, whereas the vector autoregression model of order p – VAR(p) – for multivariate system.

Both Bitcoin and Ethereum show efficiency in the weak form on the main platforms in each market alone. However, when estimating a VAR(p) between prices among exchanges, there was evidence of Granger causality between cryptocurrencies in all exchanges, suggesting that EMH is not adequate due to cross information.

It is essential to assess the cryptocurrency market in a multivariate way, not only to favor its maturation process, but also to promote a broad understanding of its inherent risks. Thus, it will be possible to develop financial products that are actively managed in a more sophisticated cryptocurrency market.

There is a possibility of performing arbitrage on different exchanges and market assets through cross-exchanges. Thus, emphasizing the need for regulation of exchanges in the digital asset market, as an eventual price manipulation on a single platform can impact others, which generates various distortions.

This study is the first to find evidence of cross-information for the same (and other) cryptocurrencies among different exchanges.

Stock markets are considered as the largest and most important units for the development and growth of the economy. The present study attempts to provide a comprehensive view of factors influencing investment decision making process of stock market investors. A multi group analysis of gender is also carried out on the proposed model.

The data of 402 valid responses are collected through structured questionnaires from individual investors of North India. SPSS 23 is used to do the descriptive analysis and AMOS 22 is used to establish the validity of the constructs and for hypotheses testing. For performing multi group analysis, several invariance tests have also been conducted to check the robustness of the model.

The results reveal that all the factors such as firm image, accounting information, neutral information, advocate recommendation and personal financial needs significantly influence investment decision making concluding image of the firm being the most influential factor and advocate recommendation being the least influential factor for investment decisions. No significant differences between males and females were found.

The current study suffers from the limitation of restricted geographical area of North India. Moreover, there is also a scope to incorporate more demographic factors for predicting investment decisions.

This study incorporates a range of factors which covers all the aspects of investment decision making. This study also highlights the notion of signaling theory, thus contributing to the limited literature in Indian context.

The purpose of this paper is to fill a gap in the literature regarding the open innovation management approaches that small and medium-sized enterprises (SMEs) can use to access digital technologies and incorporate them into their organizational processes. The research question is: What organizational and process-level managerial actions do SMEs take to successfully access and implement digital technologies within their organizational processes?

Using Guertler et al.'s (2020) Action Innovation Management Research (AIM-R) framework, this study examines the digital transformation experiences of 10 European SMEs to gain insights into the managerial actions that foster successful digital transformation.

The findings of the paper reveal two major contributions. First, a digital transformation roadmap for SMEs is proposed, with a focus on accessing external resources and reconfiguring internal ones to ease their digital transformation journey. Second, three distinct paradoxes that influence the digital transformation process in SMEs are highlighted, providing useful insights into the challenges and tensions SMEs face during this journey.

This paper provides a unique perspective on the digital transformation of SMEs by examining the managerial actions required for successful technology adoption and revealing the paradoxes that may emerge during this transformative process. The findings form the basis for future research, deepening our understanding of digital transformation in SMEs and providing actionable advice to managers and practitioners navigating this journey.