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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.

This exploratory study aims to integrate both quantitative and qualitative methods to examine the influence of contemporary university dining attributes and practices on student patronage.

First, a review of the extant literature on-campus dining in universities was conducted. Second, innovative practices of on-campus dining facilities of a large public university were identified. Finally, student perceptions of those practices were examined using a mixed method approach.

The review of literature uncovered 49 articles across 35 years on key topics such as food waste, healthy eating, and service evaluation. From site tours and interviews with related personnel, 40 innovative on-campus dining practices were identified.

Importance ratings revealed cleanliness of the environment, fresh fruit and vegetables, and digitally enabled ordering, as the top three highest rated practices. Factor analysis unveiled six factors that students find important: food diversity, good standards, innovativeness, quick options, menu variety, and fish and seafood. The thematic analysis further revealed four overarching themes (convenience, familiarity, food offerings, and value) and 13 subthemes which complemented the quantitative results.

In addition to shedding post-pandemic light on students’ dining needs, it highlights the paucity of theory used to support extant studies and suggests a novel theoretical underpinning.

Smartphone apps collect users' personal information, which triggers privacy concerns for app users. Consequently, app users restrict apps from accessing their personal information. This may impact the effectiveness of in-app advertising. However, research has not yet demonstrated what factors impact app users' decisions to use apps with restricted permissions. This study is aimed to bridge this gap.

Using a quantitative research method, the authors collected the data from 384 app users via a structured questionnaire. The data were analysed using AMOS and fuzzy-set qualitative comparative analysis (fsQCA).

The findings suggest privacy concerns and risks have a significant positive effect on app usage with restricted permissions, whilst reputation, trust and perceived benefits have significant negative impact on it. Some app-related factors, such as the number of apps installed and type of apps, also impact app usage with restricted permissions.

Based on the findings, the authors provided several implications for app stores, app developers and app marketers.

This study examines the factors that influence smartphone users' decisions to use apps with restricted permission requests. By doing this, the authors' study contributes to the consumer behaviour literature in the context of smartphone app usage. Also, by explaining the underlying mechanisms through which the principles of communication privacy management theory operate in smartphone app context, the authors' research contributes to the communication privacy management theory.

While the monetary returns to education are well documented in the economics literature, the studies on non-monetary returns to education are scarce. The purpose of this study is to provide new insights into the non-market outcomes by exploring how education influences the food consumption choices of households and how these effects vary across different socio-economic groups using household-level calorie consumption data from Sri Lanka.

This study uses two waves of Household Income and Expenditure Surveys – 2006/2007 and 2016. The methods adopted in analysing the data were descriptive statistics and the OLS regression model.

The empirical results show that educated poor households pay less per calorie compared to non-educated poor households, highlighting the role of education in improving the ability to make better food choices and manage household budgets more economically.

This study informs policy-makers of the importance of education for formulating food and nutritional policies, which aim to raise the standard of living of resource-poor and vulnerable households in Sri Lanka as well as other developing countries with similar socio-economic conditions.

To the best of the authors' knowledge, this study is the first to explore the impact of education on the calorie consumption behaviour of people in the Sri Lankan context using nationwide household surveys.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-01-2022-0007

The purpose of this paper is to determine how we ought to distinguish between reference and readers' advisory (RA) service, given the latter’s turn toward a whole collection approach. In other words, the paper answers this question: If both reference and RA librarians aim to meet patrons’ information needs and may theoretically do so using the same materials, then how are we to differentiate the two services conceptually?

In this conceptual paper, we posit that we can distinguish between RA and reference using Louise Rosenblatt’s theory of the aesthetic transaction. With this theory in hand, we can redefine the service distinction in terms of the stance – aesthetic or efferent – that the patron expects to take toward the material they seek.

On our account, the reader’s desired stance becomes a kind of hermeneutical lens through which a library worker may productively evaluate plausible pathways and materials. An aesthetic lens is characteristic of RA; it makes features of potential aesthetic transactions between a particular reader and a particular text (or genre or author’s oeuvre) salient.

The proposed account constitutes a novel application of Rosenblattian response theory, one that grounds and refines the going view that RA’s proper focus is on supporting a particular sort of experience rather than providing particular sorts of texts. This theoretical emendation also better aligns the service distinction with contemporary conceptualizations of RA as a “whole collection” service. Important practical and philosophical implications follow from the new account.

Over the years, the impact of the business cycle on firm strategy has been neglected in the area of strategic management and remains one of the most important but least developed research streams in management scholarship. Studies in this area are scattered across time and domains, therefore, there is a need to consolidate this fragmented literature to provide a comprehensive review and thus avenues for further research. This study aims to address this gap.

In this study, the systematic literature review (SLR) method is used to select and examine research articles in the area of firm responses and decisions during recession. This SLR examines 127 studies and carries out a thematic synthesis of the literature.

Based on the SLR and thematic synthesis of the literature, the themes identified in this study include – severity of recession impact (Theme 1); firm specific characteristics (Theme 2); resource adjustment activities (Theme 3); and firm performance (Theme 4), based on these themes and analysis this paper maps and proposes various relationships and linkages in this research domain that can be explored further for the development of scholarship in this field of study.

This paper fulfills the need for a systematic review of the extant literature on firms’ responses during recession. The study synthesizes literature and carries out a thematic analysis from 1980 till the period February 2024 to provide directions to advance this domain of literature.

In this paper, the authors present an empirical framework that incorporates different factors of the impact of COVID-19 on small- and medium-sized enterprises (SMEs) in La Rioja, Spain, in relation to the value chain, gender and family business and allows the evaluation of these impacts on the SMEs' outcomes.

The authors conduct exploratory research based on phone interviews with 329 business managers from SMEs in La Rioja (Spain), from June 1 to June 30 2021, using ordinary least squares linear regression and matching procedures to test the study hypotheses.

The results show that the impact of COVID-19 related to primary activities in adding value, such as inbound logistics, operations and marketing, have a positive influence on innovation outcomes in SMEs, as do female managers. Family SMEs present poorer innovation outcomes.

At the organizational level, this paper may be of interest to management, and at the national and regional levels to policymakers, since it could help to develop policies that support SMEs' sourcing, operations and marketing in order to prepare for potential value chain disruptions. Additionally, this research may help decision-makers to foster and promote innovation in SMEs as a way of ensuring their resilience.

In this paper, the authors provide novel evidence about the effect of COVID-19 in SMEs. Moreover, it has been shown that the COVID-19 pandemic has triggered the redefinition of supply chains at the organizational level.

This study investigates the relationship between child gender and a CEO’s top management hiring decisions.

Hypotheses were tested using secondary data on 121 S&P 500 male CEOs, their children, and their top management teams.

Results indicate that child gender is associated with a male CEO’s TMT hiring decisions. Specifically, we find that male CEOs with only daughters were significantly more likely to hire women to their TMTs than male CEOs with only sons and those with both sons and daughters.

This study provides evidence for the roles of familiarity, learning, and empathy in reducing gender biases in selection decisions. Top management hiring decisions have wide implications for organizational settings in general and for the breaking of the glass ceiling in particular.

Reducing gender bias in top manager hiring decisions directly relates to the United Nations’ Sustainable Development Goal 5 of achieving gender equality as women are consistently under-represented at the top of organizations across the world.

By focusing on the hiring of top managers, this study includes hiring decisions that directly impact firm operations. To our knowledge, this is the first study to examine the relationship between child gender and executive hiring decisions with a US S&P 500 sample.

In recent years, the field of financial technology (Fintech) has garnered significant attention due to advancements in technology, evolving consumer preferences and the growing need for financial services that are more accessible and user-friendly. The exponential expansion of Fintech is presenting novel prospects and obstacles for business. This study aims to investigate the relationship between gender diversity on corporate boards and firms’ performance, with a particular focus on the moderating role of Fintech.

The study sample consisted of financial sector firms listed on the Bahrain Bourse (banks and insurance firms) during the period 2016–2022. The data were gathered primarily from annual reports and the Bahrain Bourse website. The independent variable represents the percentage of female directors on corporate boards while firms’ accounting and market-based performance were measured using return on assets and Tobin’s Q variables. The moderating variable, Fintech, was measured using a checklist developed using the Global Fintech Adoption Index. Fixed effect (FE) regression was used to analyze the study data. An alternative gender diversity measure was used to test the reliability of the main regression analysis.

The results of the study indicate a positive relationship between gender diversity on corporate boards and financial performance. Additionally, the findings of the study highlighted the positive impact of Fintech practices on firms’ performance. Nevertheless, the impact of Fintech on the relationship between board gender diversity and corporate performance was found to be insignificant.

The study sample included a particular sector in a single country, which may limit the generalizability of the findings. Also, the current study applied FE regression to analyze the data; however, other econometric approaches could be used to overcome the endogeneity issue.

The findings of this study may have implications for policymakers and society, particularly in terms of promoting gender diversity and Fintech innovation.

This study contributes to the existing body of research by examining the potential impact of the percentage of female directors and the utilization of Fintech on firms’ performance in Bahrain. Given the ongoing endeavors to provide advanced Fintech solutions in the financial sector and the increasing focus on enhancing gender diversity in Bahraini corporate boards, this research aims to provide additional evidence in this domain. Moreover, this study stands out as one of the limited number of research endeavors that use Fintech as a moderating variable in the investigation of the impact of female directors on firms’ performance.

Following the recent rise in generative artificial intelligence (GenAI) tools, fundamental questions about their wider impacts have started to reverberate around various disciplines. This study aims to track the unfolding landscape of general issues surrounding GenAI tools and to elucidate the specific opportunities and limitations of these tools as part of the technology-assisted enhancement of mechanical engineering education and professional practices.

As part of the investigation, the authors conduct and present a brief scientometric analysis of recently published studies to unravel the emerging trend on the subject matter. Furthermore, experimentation was done with selected GenAI tools (Bard, ChatGPT, DALL.E and 3DGPT) for mechanical engineering-related tasks.

The study identified several pedagogical and professional opportunities and guidelines for deploying GenAI tools in mechanical engineering. Besides, the study highlights some pitfalls of GenAI tools for analytical reasoning tasks (e.g., subtle errors in computation involving unit conversions) and sketching/image generation tasks (e.g., poor demonstration of symmetry).

To the best of the authors’ knowledge, this study presents the first thorough assessment of the potential of GenAI from the lens of the mechanical engineering field. Combining scientometric analysis, experimentation and pedagogical insights, the study provides a unique focus on the implications of GenAI tools for material selection/discovery in product design, manufacturing troubleshooting, technical documentation and product positioning, among others.