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Prior studies have found that managers adjust operational activities to tackle climate risk. However, the effects of climate risk on accounting practices are largely ignored in the literature. This paper investigates whether and how climate risk influences managers’ decision-making on the level of accounting conservatism and explains the results based on two competing channels: valuation demand and contracting demand.

Using firm level climate risk measures, we build a modified Basu (1997) model to conduct our econometric tests. In the baseline model, we use earnings before extraordinary items as the dependent variable, referred to as the earnings model. We control for different levels of fixed effect to identify the shocks of climate risk and mitigate potential concerns on endogeneity and bias in the model. A series of robustness tests provide supporting evidence for our baseline results and our explanation.

Using a sample of 35,832 firm-year observations on listed US firms over the period 2002 to 2019, we find that the perception of climate risk drives managers to choose the less conservative accounting policies. We conclude that the results are consistent with the valuation demand explanation but inconsistent with the contracting demand explanation.

The study provides additional evidence on how managers respond to climate risk by adjusting their corporate polices, specifically accounting policies. Our findings contradict the results of prior studies. We explain our results from a unique perspective. Overall, the study provides valuable insights for academics, investors, managers and policymakers.

There is a knowledge gap regarding the determinants of open innovation processes and outcomes in a joint value creation context, as well as what role artificial intelligence (AI) and data management play in facilitating open innovation processes. One strategy to better understand joint value creation through open innovation, supported by AI and data management, is to conduct studies on the digital business ecosystem (DBE). The purpose of this paper is to improve our current knowledge of this urgent issue in contemporary management through the lens of an ecosystem-based theory by conducting an empirical study on two DBEs (called ecosystem micro-communities (EMCs)), developed by Haier, as well as multiple literature reviews on the key concepts “Haier EMC” and “digital business ecosystem”.

By building on multiple literature reviews and empirical data from a multi-year and ongoing research program driven by Haier, this study examines Haier’s EMC model for AI-driven DBEs. Secondary data were collected through iterative literature reviews on DBEs, the EMC concept and the two selected EMC cases. The empirical data were collected through a qualitative study of two Haier EMCs in China.

Haier's ecosystem micro-community concept represents a radical shift towards a more flexible, responsive and innovative cross-industry organizational structure, offering valuable lessons for business leaders and scholars. Haier’s ecosystem micro-community model, part of their RenDanHeYi philosophy and here viewed as a DBE, is a pioneering management concept that not only redefines the management of the firm and the traditional corporate structure, but also the traditional view on innovation management, business strategy, human resource management and marketing (customer centricity). The concept has therefore an important and big impact on traditional management. For scholars, the gap in understanding innovation processes in open business ecosystems is addressed by the concept. However, the concept also opens new areas for academic research, particularly in innovation management, business strategy, human resource management and marketing. The concepts further encourage more interdisciplinary research.

The DBE is a relatively new research area that will need more research. While the EMC model is promising as an effective version of a DBE, its effectiveness across different industries and organizational cultures needs to be explored further. Future research should investigate its applicability and impact in diverse business environments. To understand the EMC’s long-term impact, longitudinal studies are needed. These should focus on the sustained competitive advantages, potential market disruptions and the evolution of customer value propositions over time. Finally, considering increasing concerns about data privacy and security, future research should also explore how DBEs solve the issue of data protection and IP while promoting open innovation and value sharing.

For managers and practitioners, the EMC concept could inspire leaders to learn how to foster innovation by creating smaller, autonomous teams that can respond quickly to market changes in the form of a DBE. The concepts exemplify how value creation and capture could be enhanced for any company and even could be a new strategy in the company’s digital transformation and repositioning into a more competitive, high-end player on the market. The concept also emphasizes employee empowerment and ownership, which can lead to higher job satisfaction and retention rates. The concept can further improve companies’ adaptability and resilience by decentralizing decision-making. Finally, the micro-communities allow businesses to be more customer-centric, developing products and services that better meet specific customer needs.

The social implications could be positive, as complex social problems commonly need an ecosystem approach to develop and deliver impactful solutions. In addition, Haier’s ecosystem micro-community model seems inherently scalable and culturally adaptable.

Haier’s EMC model is well-known in the research literature and is a novel approach to DBEs, which has been proven successful and replicable in different countries and industries. Providing insights from multiple literature reviews and two unique Haier EMC cases will contribute to a better understanding of highly effective data- and AI-driven business ecosystems, as well as of determinants of open innovation processes and outcomes in a joint value creation context, as well as what role AI and data management play in facilitating open innovation processes.

To orient the commercial development of cowpeas, we identify the determinants of the value of cowpea grain sold by traders in Senegal’s local markets. We test whether the determinants differ between men and women traders and explore seasonal patterns.

We employ ordinary least squares and seemingly unrelated regressions using a nationally representative dataset of 973 traders, of whom 380 sell cowpea grain, in 99 urban and rural markets across the 14 regions of Senegal.

The value of cowpea grain sold is influenced by vendor and market characteristics but not by cowpea type. Women and men traders represent statistically distinct groups. The sales value was eight times higher during the survey season among men. Most women grain sellers are retailers, whereas men are involved in both retailing and wholesaling. The picture that emerges is that men traders are able to respond more to economic signals, such as purchase cost, credit and labor payments, perhaps because they operate on a larger scale. Sales were significantly correlated across seasons.

To support cowpea commercialization, researchers should explore the characteristics of enterprises led by women and men traders in greater depth. Sampling grain sold in markets to test genetic relationships with improved varieties would enable researchers to link market-based incentives directly to cowpea breeding.

Previous economics research about cowpea grain markets emphasized the hedonic analysis of grain characteristics to guide crop improvement. This study reveals differentiation among traders by gender and the importance of trader and market characteristics in sales value.

The study aims to fulfil two objectives, namely, to explore what dimensions comes into play in the current consumer EV purchase behaviour based on relevant literature identified in the past and to find out whether there are other reasons that are peculiar to the Indian automobile market which influenced consumers to adopt this eco-friendly technology.

Mixed method approach for collecting the primary data was used. The study was conducted in five cities across India, through a questionnaire administered to 266 existing EV owners using judgemental sampling, that included dimensions as to what made them purchase EVs (any variant whether hybrid or battery) and encouraged their green behaviour. Moreover, the survey also took care of gathering other motivational constructs that may have played a significant role in the Indian EV market. To take care of this, use of single open-ended question was done. Statistical techniques like exploratory factor analysis (EFA) and Partial Least Square-Structural Equation Modelling (PLS-SEM) version 4.0 were performed to gain meaningful insights from this investigation.

Based on our analysis, EV purchase behaviour in the Indian market could be explained by six configurational paths identified in conceptual framework of this study. The data analysed revealed long-term operational benefits or relative advantages, trialability or prior driving experience and positive attitude towards EVs playing an important role towards EV purchase decision followed by environmental concern, social norms and personal values of Indian consumers. Besides, several other factors were identified in open comments like favourable government policies, brand consciousness, compatibility and functional benefits in terms of comfortable and noiseless driving which tend to drive the decision of Indian consumers towards buying EVs. The identification of these motivations can help policymakers in targeting the customer market accordingly.

Although the study is restricted by its scope of sampling criteria, yet is distinct in its methodological approach and thereby adds value to existing literature on marketing and diffusion of EVs. The study explores the untapped gap in the current literature by helping identify reasons on the basis of which consumers made their choices of different EVs. Instead of analysing the potential antecedents of EV uptake, the study brings to light the actual reasons of EV purchase behaviour in the context of an emerging economy like India. That is to say, the horizon of EV motivations spans across technological, individual and regulatory attributes in the Indian automobile market.

This study is relevant and fulfils the underlying gap in the existing literature related to actual motivations that consumers look for before buying a high involvement product such as EVs. The results can be beneficial for marketers to design effective marketing strategies from the perspective of consumers. Promotional strategies addressing ease of using EVs and how battery technology is better than before needs to be clearly communicated by the marketers. Consumer education is necessary, in this regard, to make people aware of the rising air pollution levels. They have to be made understood the real advantages of owning EVs and how these non-conventional vehicles are far better when compared to traditional cars. In a nutshell, the study underscored potential determinants or reasons that made Indian consumers to go for EVs, based on statistically significant evidences which can be crucial for stakeholders operating in the Indian EV industry.

The study has important implications for members of the community. By sacrificing their egoistic tendencies or individual preferences for energy intensive products such as ICE based vehicles, people can imbibe altruistic orientation and can contribute to the collective benefit of all by shifting towards energy rich vehicles powered by electricity. This is necessary to achieve the broader goals of sustainable development and to curtail the rising climate change phenomenon.

The study applied both quantitative (deductive) and qualitative (inductive) approach to study into the reasons for consumers’ purchase motivations towards electric cars. Taking a distinct methodological approach, the study enhances the knowledge on EVs by asking consumers to comment in their own words as to why they purchased EVs. This was necessary so as to better explore the needs of the Indian automobile market and which factors govern the purchase of EVs in domestic market. Past literature majorly focused on purchase intention towards EVs but this study in unexampled and analysed the purchase behaviour towards EVs. It should be noted that our investigation reveals the complexity of EV purchase reasons than those identified in past literature and it adds to the current pool of literature on EVs by explaining factors with unrivalled illustrative power.

This paper aims to understand consumption values buying from informal retail markets (i.e., street vendor retailing). It also explores why consumers prefer daily necessary goods from the informal compared to the formal retail market (such as supermarkets, retail chain outlets and e-commerce).

Employing the qualitative research approach, this study collected data from nine respondents in two areas in Malaysia. Data were collected using semi-structured interviews and analysed using the thematic analysis technique. Only representative verbatim codes were presented under five themes of consumption value theory.

Consumers are triggered by the convenience, ease, and exclusive products (conditional value), friendly and known relationship with informal sellers, as well as the availability of some particular food items (emotional value) and lower price and freshness of groceries (functional value) while buying from informal compared to formal retail vendor.

This study provides knowledge implications to the consumption value theory. Functional, emotional, and conditional values are the dominant components of purchase behaviour in informal compared to formal retail channels. Social values are common, whereas epistemic value is more substantial in formal retailing.

Findings are helpful for informal retail businesses to understand consumers' buying behaviour. Informal retail owners should ensure that commodities are fresh, highly affordable and available in the local communities. Building a friendly relationship with consumers would be a key to the success of this retail sector.

Authorities should support informal sellers to set up mobile retail stores in residential areas. This effort would offer greater convenience to both parties in informal businesses and ensure informal sellers' financial and social well-being.

Despite the widespread acceptance of buying goods from informal retail vendors, research on consumption value in informal retailing is largely overlooked. Previous research primarily deals with formal market phenomena due to their size and economic contribution. Consequently, current literature lacks an understanding of why consumers prefer to buy from informal retail vendors for their daily groceries when the formal retail channel could fulfil similar needs. Using a qualitative research design, this research uncovers consumers' buying motives from informal compared to formal vendors.

This paper explores whether, in the context of university–industry (U–I) collaboration, new innovation strategies can be developed through actors' interactions, the exchange of resources and the co-creation of value for and within the system. In the context of the U–I relationship, the innovation perspective can highlight the need to develop strategies that elicit new formulas of value co-creation, which then facilitate innovation as a result of actor collaboration.

A total of 45 public universities in Spain, representing 95% of the total, participated in qualitative research. Personal in-depth interviews with technology transfer officers (TTOs) were conducted by an external firm; in a second phase, two of the researchers conducted eight interviews with the directors of TTOs in those universities with higher rates of transfer.

Findings reveal that enterprises with a technological focus are strengthening their relationships with universities and attempting to build a university business ecosystem by designing strategies for value co-creation such as co-ownership, co-patenting, and co-invention.

The empirical research is conducted in Spain, and results should be interpreted according to this context. Future research should examine new contexts (other countries) to improve the robustness of the data and enrich the results, thus enabling generalization of the management consequences.

The results provide a means to design strategies under a new collaborative and innovating logic. The theoretical framework contributes to theory, with implications for management.

The purpose of this paper is to investigate the factors influencing the development of social media marketing strategy in an international context. We specifically look at the potential drivers and barriers throughout the social media marketing strategy development process and how cultural differences shape social media marketing strategy decision-making among firms in international markets.

The study is conducted with an inductive research approach involving in-depth interviews with 32 firms from Finland, China and Brazil. Using inductive data analysis, we identify both internal and external factors that drive and hinder the development of firms’ social media marketing strategies. Moreover, we explore the essential elements in social media marketing strategy development based on the key practices observed among these firms, which enables us to conduct a comparative analysis of how cultural values influence the development of social media marketing strategies.

Our findings underscore the importance of both internal (i.e. resources and capabilities) and external (i.e. market-level and country-level) factors that influence the development of social media marketing strategy. Our analysis also unveiled four key practices throughout the social media marketing strategy development process: social selling, content marketing, risk management and relationship management. Additionally, we identified three distinct mindsets regarding firms’ social media selling objectives across companies in the three countries.

The comparative approach provides novel insight into firms' international social media marketing strategy. Our proposed conceptual model shows the development process of social media marketing strategy in the international context. The research propositions highlight the role of cultural values and open up new avenues for future research.

This study aims to explore and segment consumer preferences for electric and hybrid vehicles in Germany, Sweden, the Netherlands and Turkey, focusing on understanding the various factors that influence consumer decisions in these markets.

Using latent class analysis (LCA) on data collected through online surveys and discrete choice experiments, this research categorizes consumers into distinct segments. The approach allows for a nuanced understanding of how various factors such as income level, fuel cost, age, CO₂ emissions, purchase price, vehicle range, policy policies and environmental concerns interact with shape consumer preferences.

The analysis uncovers significant heterogeneity in consumer preferences for electric and hybrid vehicles across Germany, Sweden, the Netherlands and Turkey, revealing four key segments: “Eco-Driven Innovators,” “Value-Focused Pragmatists,” “Tech-Savvy Early Adopters” and “Reluctant Traditionalists.” “Eco-Driven Innovators” prioritize environmental benefits and are less sensitive to price, demonstrating a strong inclination toward vehicle CO₂ emissions and policy policies. “Value-Focused Pragmatists” weigh economic factors heavily, showing a sharp interest in fuel costs and purchase prices but are open to considering electric and hybrid vehicles if they present clear long-term savings. Technology-savvy early adopters are attracted by the latest technological advancements in vehicles, regardless of the type, and are motivated by factors beyond just environmental concerns or cost savings. Lastly, “Reluctant Traditionalists” exhibit minimal interest in electric and hybrid vehicles due to concerns over charging infrastructure and upfront costs. This detailed segmentation illustrates the diverse motivations and barriers influencing consumer choices, from governmental policies and environmental concerns to individual financial considerations and technological appeal.

This study stands out for its pioneering application of LCA to dissect the complexity of consumer preferences for electric and hybrid vehicles, a methodological approach not widely used in this research domain. Using LCA, the authors are able to uncover nuanced consumer segments, each with distinct preferences and motivations, providing a depth of insight into market dynamics that traditional analysis methods may overlook. This approach enables a more granular understanding of how diverse factors – ranging from environmental concerns to economic considerations and technological attributes – interact to shape consumer choices in different countries. The findings not only fill a critical gap in the existing literature by mapping the intricate landscape of consumer preferences, but also offer a novel perspective on strategizing market interventions. Therefore, the application of LCA enriches the discourse on sustainable transportation, offering stakeholders, manufacturers, policymakers and researchers – a refined toolkit for navigating the evolving market dynamics and fostering the adoption of electric and hybrid vehicles.

This chapter first reviews the central banks' two key remits, monetary stability and financial stability, and examines how they will be affected either directly or indirectly by the emerging challenges relating to walled gardens, shadow banking, singleness of the money, customers' data rights, artificial intelligence (AI) ethics, cybersecurity and financial exclusion. This chapter will then review three possible areas of responses that the central banks might take to address the emerging challenges: (1) regulations, (2) promotion of open digital infrastructures and (3) central banks' capabilities upgrade. This chapter will then review possible tools that the central banks might use to implement actions in those three key areas.

The primary objective of this research is to explore the potential of utilizing Global Consciousness Project (GCP) data as a tool for understanding and predicting market sentiment. Specifically, the study aims to assess whether incorporating GCP data into econometric models can enhance the comprehension of daily market movements, providing valuable insights for traders.

This study employs econometric models to investigate the correlation between the Standard & Poor's 500 Volatility Index (VIX), a common measure of market sentiment and data from the GCP. The focus is particularly on the largest daily composite GCP data value (Max[Z]) and its significant covariation with changes in VIX. The research employs interaction terms with VIX and daily returns from global markets, including Europe and Asia, to explore the relationship further.

The results reveal a significant relationship with the GCP data, particularly Max[Z] and VIX. Interaction terms with both VIX and daily returns from global markets are highly significant, explaining about one percent of the variance in the econometric model. This finding suggests that variations in GCP data can contribute to a better understanding of market dynamics and improve forecasting accuracy.

One limitation of this study is the potential for overfitting and P-hacking. To address this concern, the models undergo rigorous testing in an out-of-sample simulation study lasting for a predefined one-year period. This limitation underscores the need for cautious interpretation and application of the findings, recognizing the complexities and uncertainties inherent in market dynamics.

The study explores the practical implications of incorporating GCP data into trading strategies. Econometric models, both with and without GCP data, are subjected to an out-of-sample simulation where an artificial trader employs S&P 500 tracking instruments based on the model's one-day-ahead forecasts. The results suggest that GCP data can enhance daily forecasts, offering practical value for traders seeking improved decision-making tools.

Utilizing data from the GCP is found to be advantageous for traders as noteworthy correlations with market sentiment are found. This unanticipated finding challenges established paradigms in both economics and consciousness research, seamlessly integrating these domains of research. Traders can leverage this innovative tool, as it can be used to refine forecasting precision.