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This study aims to explore how an organization’s ethical climate determines the type and effectiveness of entrepreneurial marketing activities. Also, this study seeks to identify the most critical intra-organizational capabilities related to entrepreneurial marketing components and explain their role in the path of ethical climate to entrepreneurial marketing, which means moving from the intra- to the extra-organizational environment.

Data were collected from managers working in 100 scientific and research companies in Iran through survey questionnaires. Latent variable structural equation modeling was used to test the hypothesized relationships.

The findings reveal that the linkage between the ethical climate of the organization and entrepreneurial marketing is partially mediated by work engagement. In addition, the mediating role of knowledge transfer was not confirmed. These results imply that the ethical climate of the organization fosters entrepreneurial marketing by enabling employees with absorption, vigor and dedication.

Scientific and research companies in this research are different in size, resources, knowledge management system, organizational structure and products offered to the market; they have different emphasis on innovation and entrepreneurship as well. This issue increases the variety of data and the ability to generalize the results. Still, on the other hand, it reduces the ability to categorize data and increases the amount of outlier data. Future research in a comparative manner between different industries is needed.

This study indicates that an organization’s ethical climate can be a critical predictor of its entrepreneurial marketing as well as effective knowledge transfer and work engagement. In this regard, organizations should pay attention to employee’s perception of the organization’s ethical climate and create an environment that supports productive behaviors, commitment, trust, communication, work dedication, etc., to facilitate knowledge transfer effectively so that the organization can identify market opportunities and turn it into customer-oriented innovation, cocreate value for their customers and increase market share.

In turbulent markets, companies need to introduce quality and reliable products. Still, because the life cycle of products has shortened and the speed of introducing new products has increased, the supply of products will fail if companies are not equipped with new marketing methods. In this regard, the current research will seek to provide a mechanism for organizational capabilities on the road to entrepreneurial marketing by expressing entrepreneurial marketing as an innovative approach and trying to identify factors affecting it.

The resource-based view (RBV) emphasises the importance of resources for firm performance. However, recent research argues that the focus on firm performance should also be based on inside-out (IO) and outside-in (OI) capabilities. Specifically, we study the importance of resources on product development (an IO) and market driving (an OI) entrepreneurial marketing capabilities on entrepreneurial firm performance in an emerging market. The study further investigates the moderating effects of marketing agility on the relationship between resources and capabilities.

The study is based on survey data of a multi-industry sample of 102 entrepreneurial firms in Pakistan.

The results show that marketing agility moderates the relationship between resource-mix flexibility on product development and market driving capabilities, but it only positively moderates the relationship between resource-mix inimitability and product development capability. Marketing driving and product development capabilities play a role as parallel mediators between resources and firm performance.

The study lies at the intersection of marketing and entrepreneurship literature by (1) providing a nuanced understanding of marketing agility as a boundary spanning factor for IO and OI entrepreneurial marketing capabilities; (2) integrating the resource types and product development from IO and market-driving from OI capabilities perspectives; (3) identifying the effects of IO and OI on firm performance providing guidance for entrepreneurs seeking improved firm performance.

This paper seeks to demonstrate the value of using social media to capture fashion trends, including the popularity of specific features of clothing, in order to improve the speed and accuracy of supply chain response in the era of fast fashion.

This study examines the role that text mining can play to improve trend recognition in the fashion industry. Researchers used n-gram analysis to design a social media trend detection tool referred to here as the Twitter Trend Tool (3Ts). This tool was applied to a Twitter dataset to identify trends whose validity was then checked against Google Trends.

The results suggest that Twitter data are trend representative and can be used to identify the apparel features that are most in demand in near real time.

The 3Ts introduced in this research contributes to the field of fashion analytics by offering a novel method for employing big data from social media to identify consumer preferences in fashion elements and analyzes consumer preferences to improve demand planning.

The 3Ts improves forecasting models and helps inform marketing campaigns in the apparel retail industry, especially in fast fashion.

Chinese firms are winning market share from foreign multinational enterprises in domestic markets. The international business literature suggests that this is happening because these firms are developing non-traditional firm-specific advantages (FSAs). Strategic factor market (SFM) theory provides a good basis for explaining how this is happening. However, it is underdeveloped in terms of analysing unique resources and unique access to those resources by Chinese firms in their domestic markets. This paper aims to develop a framework to understand how Chinese firms have developed non-traditional FSAs.

The case study method is adopted to explore how Chinese firms develop non-traditional FSAs. Specifically, the authors compare paired case studies of a Chinese firm and a foreign multinational in each of two industries.

The authors find that Chinese firms have developed non-traditional FSAs because of more relevant experience, better adapted strategies and privileged relationships. This has enabled Chinese firms to develop non-traditional FSAs.

The authors propose a framework that conceptualises non-traditional FSA development in Chinese firms as a product of superior access to unique and valuable resources in their domestic SFMs.

Given the heated academic and policy debate regarding the fate of garment manufacturing in a high-wage developed economy in the 21st century, this study aims to explore the production and export strategies of apparel “Made in Ireland.”

A logistic regression analysis of 4,000 apparel items at the stock keeping unit (SKU) level sold in the market from January 2018 to December 2021 was conducted to evaluate the production and export strategy of apparel “Made in Ireland” versus foreign-made imported items sold in Ireland.

The statistical results showed that Ireland’s apparel manufacturing sector survived the market competition by leveraging non-price competing factors, such as distinct product assortment, cultural heritage, history and traditional craftsmanship.

The findings challenged the conclusions of the classic trade and economic development theories regarding the trajectory of the garment manufacturing sector and called for a rethink about the strategies for expanding garment manufacturing in a high-wage developed country in today’s global economy.

This study examines the motivational processes of charged behavior and collective efficacy driving interdependence and agency in new product development (NPD) teams and the moderating impact of team risk-taking propensity as affective, cognitive and behavioral social processes support team innovation.

Data were collected from 92 NPD teams engaged in B2C and B2B product and service development. Mediating and moderating effects are examined using partial least squares structural equation modeling, referencing social cognitive and collective agency theories as the research framework.

The analysis validates collective self-efficacy and charged behavior as interdependent motivational–affective processes that align cognitive resources and govern team effort toward innovativeness. Teams' risk-taking propensity regulates behavior, and collective efficacy facilitates self-regulated motivational engagement. Charged behavior cultivates the emotional contagion, team identification, cohesion and adaptation required for team functioning. Team potency fosters cohesiveness, while team learning improves adaptability along the innovation journey. The resulting theory asserts that motivational drivers enhance the interplay between cognitive and behavioral processes.

Managers should consider NPD teams as social systems with a capacity for collective agency nurtured through interdependence, which requires collective efficacy and shared competencies to generate motivational purpose and innovativeness. Managers must remain mindful of teams' risk tolerance as regulating the impact of motivational factors on innovativeness.

This study contributes to research on the motivational–affective drivers of NPD charged behavior and collective efficacy as complementary to cognitive and behavioral processes sustaining team innovativeness.

This study aims to address the aspects of product and process innovation strategies and their determining factors to understand their characteristics in clothing manufacturing and contribution for a successful and competitive clothing industry.

This general review is based on literature data of previous studies on innovation that transcend and cover the aspects of innovation applicable in the clothing industry. Although the scope of discussion is theoretically broad, it focusses on the context of innovation strategies in clothing manufacturing and the determinant factors indicating the acquisition and implementation of product and process-related innovation activities, simultaneously exploring and linking their implications for adopting, managing and integrating enterprise activities to the values of desired innovation novel models.

Based on theoretical background and pragmatic generalizations, product and process innovation strategies in clothing manufacturing firms tend to incline more towards computer-integrated technologies and concepts meant to promote product development, process optimization and organizational integration. Industry, technological and R&D factors tend to significantly determine innovation capability of a clothing firm.

This review generates integrated conceptual frameworks for product and process innovation strategies applicable in clothing firms and their determinant factors as prelude to empirical validation.

Even the greatest developed countries have capitulated to the destructions imposed on the global supply systems, as the COVID-19 pandemic has revealed. The purpose of this study is to explore human resource sourcing strategies for managing supply chain performance during the COVID-19 outbreak. There are six human resource sourcing strategies such as outsourcing, near sourcing, integration, the requirement of suppliers, joint ventures and virtual enterprise that are considered to measure supply chain performance.

Based on collecting data from the potential respondents of Indian manufacturing companies, the elevation of human resource sourcing strategies to supply chain performance is measured considering the multiple regression analysis techniques.

The results of the study revealed that four of the six hypotheses have a significant and positive relationship with supply chain performance during the COVID-19 outbreak while two hypotheses are partially supported that lent good support to this study.

In this critical situation, this study will enable managers and practitioners to support the business in giving customers the best services on time.

The novelty of this study is to identify the key human resource sourcing strategies by using multiple regression analysis methods, considering the case of Indian manufacturing companies to measure their supply chain performance during the COVID-19 outbreak era.

Drawn from the push–pull perspective, this research aims to identify the determinants of Chinese technology's outward foreign direct investments (OFDI) into the Eurasian region.

The authors argue that contrary to the extant literature, technology-driven OFDI from emerging-market multinationals (EMNEs) do not always seek developed countries, and EMNEs' technology investments in emerging economies are rising indicating that there are factors in these economies that can prove attractive. The authors recognize the influence of the macroeconomic environment and the interaction of home and host-country institutional contexts that influence the location choice of EMNEs technology-driven OFDI into other emerging economies, mediated by the industry sector and firm's ownership structure. The authors test our hypotheses using a sample of 1,656 observations of Chinese MNEs' tech-investments in the Eurasian region from 2005 to 2019.

The study results indicate that bilateral diplomatic relations pave the way of the host-country institutional environment for Chinese MNEs uncovering the role of the Chinese government as an OFDI facilitator. This study also unveils a lower technology level of the Chinese MNEs' investments in the Eurasian region connoting an interest in market opportunities exploitation through their existing technologies – through its comparative advantage in the global markets – rather than strategic assets acquisition aiming at augmenting their technological capabilities. This trend is similar to that of other major foreign direct investment (FDI) source countries.

This research contributes to a better understanding of the characteristics and the location choice of technology investments from EMNEs into other emerging economies that have received scant attention in the literature. In addition, it extends the institutional theory by analyzing how home-country institutions, through bilateral diplomatic relations, may smooth the host country institutional environment for home-country MNEs' foreign investments and contributes as well to the debate on the applicability of the existing theoretical framework in the case of emerging-market MNEs.

The current gap between the required and available artificial intelligence (AI) professionals poses significant challenges for organisations and academia. Organisations are challenged to identify and secure the appropriate AI competencies. Simultaneously, academia is challenged to design, offer and quickly scale academic programmes in line with industry needs and train new generations of AI professionals. Therefore, identifying and structuring AI competencies is necessary to effectively overcome the AI competence shortage.

A probabilistic topic model was applied to explore the AI competence categories empirically. The authors analysed 1159 AI-related online job ads published on LinkedIn.

The authors identified five predominant competence categories: (1) Data Science, (2) AI Software Development, (3) AI Product Development and Management, (4) AI Client Servicing, and (5) AI Research. These five competence categories were summarised under the developed AI competence framework.

The AI competence framework contributes to clarifying and structuring the diverse AI landscape. These findings have the potential to aid various stakeholders involved in the process of training, recruiting and selecting AI professionals. They may guide organisations in constructing a complementary portfolio of AI competencies by helping users match the right competence requirements with an organisation's needs and business objectives. Similarly, they can support academia in designing academic programmes aligned with industry needs. Furthermore, while focusing on AI, this study contributes to the research stream of information technology (IT) competencies.