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The purpose of this paper is to examine the role of founding team experience (industry and venturing) in new venture creation. This paper posits the following questions: How does founding team experience influence the likelihood of new venture creation, in the nascent stage? How does industry context moderate this relationship? The study aims to fill an important gap in the literature by unpacking the impact of different types of founding team experiences on venture outcome, and by focusing on the influence of founding team in the venture creation process, specifically at the nascent stage.

The paper utilizes data from the Second Panel Study of Entrepreneurial Dynamics, a longitudinal data set of 1,214 nascent entrepreneurs in the USA. Logistics regression was employed to analyze the effect of founding team experience on new venture creation. Post hoc analysis was conducted to ensure the confidence of the findings.

The paper provides empirical insights about how founding team experience influences the likelihood of new venture creation in the nascent stage. At the nascent stage, founding team industry experience positively affects new venture creation while founding team venturing experience does not. However, in the high-technology industry environment, the influence of the founding team’s venturing experience on new venture creation is stronger than that in the low-technology industry environment.

Due to the design of the data set, there is a risk of “right-censoring” problem. Also, because the study used archival data on founding teams, the methodology did not allow for uncovering the underlying team processes and dynamics during the venture creation process based on learning from experience. Future studies are encouraged to examine other types of founding team experience and the underlying process-level factors on venture creation.

The paper provides important practical implications for nascent entrepreneurs/entrepreneurial teams on team assembling and composition. In general, a team with higher-level industry experience is critical for venturing success. A team with higher-level venturing experience is more desired in the high-technology industry.

This paper fulfills an important gap in the entrepreneurial team literature by highlighting the complex and nuanced ways in which founding team experience influences the likelihood of venture creation in the nascent stage of the firm, especially after incorporating the additional impact of the industry context.

This paper examines the network dynamics of the cross-border trades utilizing Social Network Analysis (SNA) based on data obtained from the WTO-OECD Trade in Value Added database from 2000-2011. The main results of this paper are as follows: regarding the top 10 in-degree centrality industries, industries in China, Germany, and the U.S. have emerged as the largest importers of foreign value added, implying that the global production network is dominated by two different types of industries. The first type includes processing and assembling functions in China and Germany. The other type of industry involves foreign value added largely for domestic final demand in the U.S. Secondly, there are also two types of brokerage roles. U.S. industries are operating in a liaison role, while Chinese and German industries are mostly operating as coordinator or gatekeeper. Thirdly, manufacturing industries in China and Germany which have emerged as higher in-degree centrality incur a large portion of their value added from the logistics industry. This suggests that those leading industries with the highest characteristics of hubness in the global production network cannot sustain their network status without efficient utilization of the logistics industry.

The purpose of this paper is twofold: first, to investigate the relationship between some characteristics of corporations including firm size, financial leverage, profitability, firm age and the type of industry with social responsibility disclosure of firms listed on Tehran Stock Exchange (TSE); and second, to study the association between the level of corporate social responsibility disclosure (CSRD) and some of the audit variables such as audit fees, audit tenure and audit firm’ size.

The study population consists of 125 firms listed on the TSE during the years 2010–2015. Following Salehi et al. (2017), content analysis is used to measure the level of social responsibility disclosure, and hypotheses are performed using multiple regression analysis and R software.

The results represented that there is a positive significant relationship between a firm size and a firm age with the level of CSRD. However, there is a negative significant association between financial leverage and profitability with the level of CSRD. Given that CSRD is different among various industries and the type of industry can be an influential factor in CSRD, an industry type’ variable in the fourth hypothesis is of a type of index variable and has eight levels, of which the first level is ranked as the base level. Our findings showed that the level of CSRD at industries of machinery and appliances, production of metal products, food and beverage products, and textiles is lower than the baseline level (pharmacy). Nevertheless, companies in the fifth industry (mineral products) have a higher level of CSRD in comparison with the pharmacy industry. Moreover, the authors find that there is a significant positive connection between audit fees and CSRD. This implies that Iranian managers in an inflationary economy probably manage earnings when they provide more CSRDs, which leads to increase in the audit risk and audit fees.

Needless to say, the findings of this paper will have practical implications for investors, auditors and other users of financial statements. First of all, this study will aware them of the fact that when a country faces economic sanctions and most of its companies are in financial strain investors should not consider the firms engaging in corporate social responsibility activities to behave morally and provide transparent financial reports. Second, the results will convince auditors to be conservative toward the firms that are financially distressed, for audit risk of them will be high. Thus, policymakers should be cautious concerning directors’ opportunistic actions and increase monitoring to enforce social obedience.

The turning point of this research is related to the time period of research related to firms that have faced severe financial problems due to economic sanctions. In fact, the study revealed another aspect of CSRD that could have negative consequences when managers are in financial strain and take opportunistic actions.

Industry 4.0 technologies are promising to increase manufacturing companies' performance through the new knowledge that such digital technologies allow to create and manage within the firm boundaries and through customer interactions. Despite the great attention on the Industry 4.0 adoption paths, little is known about the relationships with previous waves of digital technologies, namely, information and communication technologies (ICTs), and how different groups of both types of technologies link to knowledge and its related performances.

The study employed a quantitative research design using a survey method. Submitting the questionnaire to entrepreneurs, chief operation officers or managers in charge of the operational and technological processes of Italian manufacturing firms, 206 respondents stated that their firm has adopted at least one of the seven Industry 4.0 technologies investigated.

The findings of the study highlight the positive relationship between ICT and Industry 4.0 technologies in terms of both intensity and groups of technologies (Web-based, Management and Manufacturing ICT; Operation, Customization and Data-processing 4.0), and how technologies affect knowledge-related performances in terms of products and processes, job-learning, product-related services and customer involvement.

This study is one of the first attempts to link groups of ICT to groups of Industry 4.0 technologies and to explore the effects in terms of knowledge-related performances as a measure of technology use. The study shows strong path dependency among ICT, Industry 4.0 and knowledge performance, enriching the literature on technological innovation and knowledge management.

This paper aims to find the best tools to influence the improvement of sustainability in food supply chains (FSCs) by conducting a systematic review of articles. The reader will learn how the different industry 4.0 tools (I4.0T) benefit the FSC and the limitations of each tool.

A review of 436 articles published during the period 2019 to 2022 referenced in the Scopus and Web of Science databases was performed. The review was limited to articles published in English and directly related to Industry 4.0, circular economy and sustainability in the food supply chain.

The results show different contributions of I4.0, with some being more influential than others in improving sustainability in FSCs; for example, Internet of Things and Blockchain have been shown to contribute more toward transparency, traceability, process optimization and waste reduction.

The paper's contribution consisted of ranking according to their importance and the I4.0T that affect sustainability in FSCs by classifying the aspects of each tool and the sustainability factors through a categorization by the Analysis Hierarchy Process.

Many manufacturers are exploring adopting smart technologies in their operations, also referred to as the shift towards “Industry 4.0”. Employees' contribution to high-tech initiatives is key to successful Industry 4.0 technology adoption, but few studies have examined the determinants of employee acceptance. This study, therefore, aims to explore how managers affect employees' acceptance of Industry 4.0 technology, and, in turn, Industry 4.0 technology adoption.

Rooted in the unified theory of acceptance and use of technology model and social exchange theory, this inductive research follows an in-depth comparative case study approach. The two studied Dutch manufacturing firms engaged in the adoption of Industry 4.0 technologies in their primary processes, including cyber-physical systems and augmented reality. A mix of qualitative methods was used, consisting of field visits and 14 semi-structured interviews with managers and frontline employees engaged in Industry 4.0 technology adoption.

The cross-case comparison introduces the manager's need to adopt a transformational leadership style for employees to accept Industry 4.0 technology adoption as an organisational-level factor that extends existing Industry 4.0 technology user acceptance theorising. Secondly, manager's and employee's recognition and serving of their own and others' emotions through emotional intelligence are proposed as an additional individual-level factor impacting employees' acceptance and use of Industry 4.0 technologies.

Synthesising these insights with those from the domain of Organisational Behaviour, propositions were derived from theorising the social aspects of effective Industry 4.0 technology adoption.

Literature repeatedly complains about the lack of empirical data on the costs of cyber incidents within organizations. Simultaneously, managers urgently require transparent and reliable data in order to make well-informed and cost-benefit optimized decisions. The purpose of this paper is to (1) provide managers with differentiated empirical data on costs, and (2) derive an activity plan for organizations, the government and academia to improve the information base on the costs of cyber incidents.

The authors analyze the benchmark potential of costs within existing literature and conduct a large-scale interview survey with 5,000 German organizations. These costs are directly assignable to the most severe incident within the last 12 months, further categorized into attack types, cost items, employee classes and industry types. Based on previous literature, expert interviews and the empirical results, the authors draft an activity plan containing further research questions and action items.

The findings indicate that the majority of organizations suffer little to no costs, whereas only a small proportion suffers high costs. However, organizations are not affected equally since prevalence rates and costs according to attack types, employee classes, and other variables tend to vary. Moreover, the findings indicate that board members and IS/IT-managers show partly different response behaviors.

The authors present differentiated insights into the direct costs of cyber incidents, based on the authors' knowledge, this is the largest empirical survey in continental Europe and one of the first surveys providing in-depth cost information on German organizations.

The purpose of this paper is to test the influences of audit committee’s and company’s characteristic on intellectual capital disclosure (ICD) among the LQ45-listed companies in Indonesia Stock Exchange (BEI) between 2013 and 2014.

The paper employed multiple linear regression and saturation sample as the analysis methods.

The findings showed that size of audit committee does not significantly influence ICD; meeting frequency of audit committee positively influences ICD; and company size does not influence ICD positively. On the other hand, profitability does not significantly influence ICD; leverage has negative and significant influence on ICD; and the type of industry does not significantly influence intellectual capital disclosure.

As there are few ICD studies, this research will surely add ICD antecedents to literature.

The real estate industry has experienced frequent changes in corporate executives in recent years. A total of 147 A-share listed firms witnessed a total of 191 corporate executives' departure. This wave of corporate executive departures is significantly different from previous waves. This study aims to examine whether industry evolution influence the characteristics of corporate executives? If so, then how?

Drawing on upper echelons theory, this study analyzed the effects of industry life cycle on the characteristics of corporate executives. The data of A-share listed companies in the textile, real estate and computer industries in China from 1992 to 2014 were collected.

There are significant differences in the characteristics of corporate executives that match the life cycles of different industries. Companies at the growth stage in the life cycle of an industry were more likely to select and appoint younger corporate executives with political capital, peripheral functions and output functions, whereas companies at the maturity stage were more likely to select and appoint older corporate executives with throughput functions.

By using the upper echelons theory as a starting point, this study analyzed the effects of industry life cycle on corporate executive's characteristics. The research findings offer theoretical implications for the upper echelons theory and provide managerial implications.

The purpose of this study is to explore the potential and growth of big data across several industries between 2016 and 2020. This study aims to analyze the behavior of interest in big data within the community and to identify areas with the greatest potential for future big data adoption.

This research uses Google Trends to characterize the community’s interest in big data. Community interest is measured on a scale of 0–100 from weekly observations over the past five years. A total of 16 industries were considered to explore the relative interest in big data for each industry.

The findings revealed that big data has been of high interest to the community over the past five years, particularly in the manufacturing, computers and electronics industries. However, over the 2020s the interest in the theme decreased by more than 15%, especially in the areas where big data typically had the greatest potential interest. In contrast, areas with less potential interest in big data such as real estate, sport and travel have registered an average growth of less than 10%.

To the best of the author’s knowledge, this study is original in complementing the traditional survey approaches launched among the business communities to discover the potential of big data in specific industries. The knowledge of big data growth potential is relevant for players in the field to identify saturation and emerging opportunities for big data adoption.