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Reverse logistics services are designed to move goods from their point of consumption to an endpoint to capture value or properly dispose of products and materials. Artificial intelligence (AI)-based reverse logistics will help Micro, Small, and medium Enterprises (MSMEs) adequately recycle and reuse the materials in the firms. This research aims to measure the adoption of AI-based reverse logistics to improve circular economy (CE) performance.

In this study, we proposed ten hypotheses using the theory of natural resource-based view and technology, organizational and environmental framework. Data are collected from 363 Indian MSMEs as they are the backbone of the Indian economy, and there is a need for digital transformation in MSMEs. A structural equation modeling approach is applied to analyze and test the hypothesis.

Nine of the ten proposed hypotheses were accepted, and one was rejected. The results revealed that the relative advantage (RA), trust (TR), top management support (TMS), environmental regulations, industry dynamism (ID), compatibility, technology readiness and government support (GS) positively relate to AI-based reverse logistics adoption. AI-based reverse logistics indicated a positive relationship with CE performance. For mediation analysis, the results revealed that RA, TR, TMS and technological readiness are complementary mediation. Still, GS, ID, organizational flexibility, environmental uncertainty and technical capability have no mediation.

The study contributed to the CE performance and AI-based reverse logistics literature. The study will help managers understand the importance of AI-based reverse logistics for improving the performance of the CE in MSMEs. This study will help firms reduce their carbon footprint and achieve sustainable development goals.

Few studies focused on CE performance, but none measured the adoption of AI-based reverse logistics to enhance MSMEs’ CE performance.

This study employs Stein Rokkan's methodological approach to analyse state formation in the Greater Middle East. It develops a conceptual framework distinguishing colonial, populist and democratic pacts, suitable for analysis of state formation and nation-building through to the present period. The framework relies on historical institutionalism. The methodology, however, is Rokkan's. The initial conceptual analysis also specifies differences between European and the Middle Eastern state formation processes. It is followed by a brief and selective discussion of historical preconditions. Next, the method of plotting singular cases into conceptual-typological maps is applied to 20 cases in the Greater Middle East (including Afghanistan, Iran and Turkey). For reasons of space, the empirical analysis is limited to the colonial period (1870s to the end of World War 1). Three typologies are combined into one conceptual-typological map of this period. The vertical left-hand axis provides a composite typology that clarifies cultural-territorial preconditions. The horizontal axis specifies transformations of the region's agrarian class structures since the mid-19th century reforms. The right-hand vertical axis provides a four-layered typology of processes of external intervention. A final section presents selected comparative case reconstructions. To the authors' knowledge, this is the first time such a Rokkan-style conceptual-typological map has been constructed for a non-European region.

While existing literature extensively explores manufacturing firms expanding into services, little is known about the modes of servitisation, the means by which they carry it out. This paper concentrates on acquisitions as a mode of servitisation. Post-acquisition integration is when the potential of an acquisition is realised. The paper therefore aims to categorise types of integrations following the acquisition of servitised firms and discusses their consequences for servitisation.

The empirical part of the paper is based on two case studies, each involving the acquisition of servitised firms. Both acquirers changed their integration approach over time.

The paper conceptualises three types of integrations: rhetorical, insulated and transformative integrations, indicating whether and how the acquirer becomes servitised following the integration. These highlight the analysis of integration based on business models and customer orientation in relation to servitisation.

This paper contributes to research on servitisation by emphasising acquisitions as a mode of servitisation and conceptualising three integration types related to business models and customer orientations. Furthermore, the paper highlights how an acquirer's servitisation leads to new offerings targeting new customers, as opposed to strengthening existing relationships.

In this paper, the heterogeneity of the linkages among financial development, productivity and growth across income groups is emphasized.

An empirical analysis is conducted with an illustrative sample of 130 economies over the period 1991–2019 and classified into four subsamples: Organisation for Economic Co-operation and Development (OECD), developing, least developed and net food importing developing countries. Forecast error variance decompositions and panel vector auto-regressive estimations are computed, with insightful findings.

Higher levels of output stimulate the economic development in the agricultural sector, mainly via the productivity channel and, in the most developed economies, also through access to credit. Differently, in developing and least developed economies, the role of access to credit is marginal. The findings have practical implications for stakeholders involved in the planning of long-run investments. In less developed economies, priorities should be given to investments in technology and innovation, whereas financial markets are more suited to boost the development of the agricultural sector of developed economies.

The authors conclude on the credit–output–productivity nexus and contribute to the literature in (at least) three ways. First, they assess how credit access, agricultural output and agricultural productivity are jointly determined. Second, they use a novel approach, which departs from most of the case studies based on single-country data. Third, they conclude on potential causality links to conclude on policy implications.

Organizations have started using the metaverse to sell non-fungible tokens, execute engineering processes and conduct business meetings. A condition of creating value by moving business processes to the metaverse is acceptance of this technology. In business-to-business scenarios, internal employees and external partners may have different views on the topic but must agree upon new practices. Understanding common motivations and challenges associated with using the metaverse is crucial to its success.

The authors interviewed managers from a pharmaceutical company considering conducting meetings with clients in the metaverse. A series of 23 statements on reasons for (non)-use was generated. Twenty-five individuals (13 employees and 12 clients) then ranked these statements against each other, revealing what would drive or hinder their metaverse use. The authors compared these perspectives to identify common issues.

The authors identified four different views. Views 1 and 2 correspond to internal and external participants, while Views 3 and 4 correspond to external ones only. View 1 is skeptical and underlines the role of peers in acceptance. View 2 is a positive perspective centered on usefulness. View 3 is ambivalent and is centered on efforts required to use the metaverse. View 4 reveals a reversed perspective wherein using the metaverse is a low-effort activity.

This paper proposes a case study probing acceptance of a realistic business use of the metaverse. This paper identifies risks to mitigate and motivations to leverage when proposing metaverse usage in a business-to-business context.

This study adopts a new macro-perspective to explore the complex and dynamic links between financial instability and the Euro-American green equity market. Its primary focus and novelty is to shed light on the non-linear and asymmetric characteristics of dependence, causality, and contagion within various time and frequency domains. Specifically, the authors scrutinize how financial instability in the U.S. and EU interacts with their respective green stock markets, while also examining the cross-impact on each other's green equity markets. The analysis is carried out over short-, medium- and long-term horizons and under different market conditions, ranging from bearish and normal to bullish.

This study breaks new ground by employing a model-free and non-parametric approach to examine the relationship between the instability of the global financial system and the green equity market performance in the U.S. and EU. This study's methodology offers new insights into the time- and frequency-varying relationship, using wavelet coherence supplemented with quantile causality and quantile-on-quantile regression analyses. This advanced approach unveils non-linear and asymmetric causal links and characterizes their signs, effectively distinguishing between bearish, normal, and bullish market conditions, as well as short-, medium- and long-term horizons.

This study's findings reveal that financial instability has a strong negative impact on the green stock market over the medium to long term, in bullish market conditions and in times of economic and extra-economic turbulence. This implies that green stocks cannot be an effective hedge against systemic financial risk during periods of turbulence and euphoria. Moreover, the authors demonstrate that U.S. financial instability not only affects the U.S. green equity market, but also has significant spillover effects on the EU market and vice versa, indicating the existence of a Euro-American contagion mechanism. Interestingly, this study's results also reveal a positive correlation between financial instability and green equity market performance under normal market conditions, suggesting a possible feedback loop effect.

This study represents pioneering work in exploring the non-linear and asymmetric connections between financial instability and the Euro-American stock markets. Notably, it discerns how these interactions vary over the short, medium, and long term and under different market conditions, including bearish, normal, and bullish states. Understanding these characteristics is instrumental in shaping effective policies to achieve the Sustainable Development Goals (SDGs), including access to clean, affordable energy (SDG 7), and to preserve the stability of the international financial system.

This paper investigates how two characteristics of language, abstractness vs concreteness and narrativity, influence user engagement in communication exercises on innovation targeted to the general audience. The proposed conceptual model suggests that innovation fits well with more abstract language because of the association of innovation with imagination and distal construal. Moreover, communication of innovation may benefit from greater adherence to the narrativity arc, that is, early staging, increasing plot progression and climax optimal point. These effects are moderated by content variety and emotional tone, respectively.

Based on a Latent Dirichlet allocation (LDA) application on a sample of 3225 TED Talks transcripts, the authors identify 287 TED Talks on innovation, and then applied econometric analyses to test the hypotheses on the effects of abstractness vs concreteness and narrativity on engagement, and on the moderation effects of content variety and emotional tone.

The authors found that abstractness (vs concreteness) and narrativity have positive effects on engagement. These two effects are stronger with higher content variety and more positive emotional tone, respectively.

This paper extends the literature on communication of innovation, linguistics and text analysis by evaluating the roles of abstractness vs concreteness and narrativity in shaping appreciation of innovation.

This paper reports conceptual and empirical analyses on innovation dissemination through a popular medium – TED Talks – and applies modern text analysis algorithms to test hypotheses on the effects of two pivotal dimensions of language on user engagement.

This study aims to investigate the association between Corporate Social Responsibility (CSR) and tax avoidance, as well as the effect of earnings performance on this link. We suggest a negative association between CSR and tax avoidance based on the Stakeholder Theory. We also suggest that earnings performance moderates this relationship. Based on a sample of 25 Tunisian firms during the years 2012–2017, data were gathered via annual reports of the companies, and a survey-questionnaire was used to gather CSR information. The research design uses ordinary least squares (OLS) regression to investigate the association between CSR and tax. In addition, the analysis is performed using panel data to account for heterogeneity at the individual level and over time. Using this research design, the study provides a comprehensive examination of the effect of CSR on tax avoidance among Tunisian companies over a 6-year period. According to our findings, companies that participate in CSR initiatives show less tax avoidance than those that do not. Moreover, in line with the Slack Resource Theory, for businesses with higher earnings, the negative link between CSR and tax avoidance is stronger. Our research demonstrates that businesses may utilize CSR to improve their standing in the community and lower the likelihood of tax avoidance. These results suggest that profitable firms may have more funds available to spend on CSR initiatives and, as a result, are more motivated to maintain a positive reputation by refraining from tax avoidance strategies.

Despite its devastating nature, the COVID-19 pandemic has also catalyzed a substantial surge in the adoption and integration of technological tools within economies, exerting a profound influence on the dissemination of information among participants in stock markets. Consequently, this present study delves into the ramifications of post-pandemic dynamics on stock market behavior. It also examines the relationship between investors' sentiments, underlying behavioral drivers and their collective impact on global stock markets.

Drawing upon data spanning from 2012 to 2023 and encompassing major world indices classified by Morgan Stanley Capital International’s (MSCI) market and regional taxonomy, this study employs a threshold regression model. This model effectively distinguishes the thresholds within these influential factors. To evaluate the statistical significance of variances across these thresholds, a Wald coefficient analysis was applied.

The empirical results highlighted the substantive role that investors' sentiments and behavioral determinants play in shaping the predictability of returns on a global scale. However, their influence on developed economies and the continents of America appears comparatively lower compared with the Asia–Pacific markets. Similarly, the regions characterized by a more pronounced influence of behavioral factors seem to reduce their reliance on these factors in the post-pandemic landscape and vice versa. Interestingly, the post COVID-19 technological advancements also appear to exert a lesser impact on developed nations.

This study pioneers the investigation of these contextual dissimilarities, thereby charting new avenues for subsequent research studies. These insights shed valuable light on the contextualized nexus between technology, societal dynamics, behavioral biases and their collective impact on stock markets. Furthermore, the study's revelations offer a unique vantage point for addressing market inefficiencies by pinpointing the pivotal factors driving such behavioral patterns.

This study aims to examine whether and why subsidiary-unit managers’ prior international work experiences across multinational enterprises’ (MNEs) home and host countries impact their subsidiary-unit performance, considering the mediating effect of their advice networks.

A survey on 222 subsidiary-unit managers (154 parent country nationals [PCNs] and 68 host country nationals [HCNs]) of a Korean MNE operating in China, Vietnam, Thailand, Singapore, Hungary and Slovakia was conducted. The authors analyzed the data using partial least square structural equation modeling, multigroup analysis and bootstrapping techniques.

PCN subsidiary managers with more prior international work experience manage better-performing units due to the strength of the manager’s advice networks across local parties. However, for HCN subsidiary managers, this study did not find such mediating roles of the size and strength of their advice networks in the MNE home country.

This study provides novel insights and empirical evidence about the effect of the length of prior international work experience of subsidiary managers on their advice-seeking networks and subsidiary-unit performance. In addition, it draws on and add to social capital theory about how international work experience impacts dealing with local businesses and the relationship with corporate headquarters.