Globalization, geopolitics, and socio-economic uncertainties increase supply chain vulnerabilities. Climate changes, natural disasters, and man-made accidents have increased the tension of disturbances. The COVID-19 pandemic has disrupted many supply chains worldwide, putting the agri-food supply chain at a higher risk than ever. Agri-food supply chains face severe and complex challenges due to industry-specific characteristics, such as perishability, short shelf life, long lead time production, and weather dependence. Consumer awareness of having healthy, traceable, and environmentally friendly food products has become an increasing concern, making sustainable development also a vital factor in the agri-food industry. To ensure sustainable development, firms must improve supply chain resilience by discovering, nurturing, and developing resilience capability and competitive advantage. Resilience describes the ability to respond quickly to disruptions and help the supply chain recover. Recently, digital technologies have developed rapidly, supported by the Industrial Revolution 4.0, which plays a crucial role in a company's operations. Digital technologies help promote core resilience competencies such as visibility, collaboration, and agility through typical technologies such as blockchain, artificial intelligence, fifth-generation technology, big data analytics, additive manufacturing, tracking, tracing technologies, etc. This study uses a theoretical framework from dynamic capabilities and extant literature reviews to determine the research gap in the agri-food industry. The study uses mixed methods: a qualitative research method to examine and uncover the role of supply chain resilience in responding to disruptions in the agri-food industry, and a second study used a quantitative method to examine the influence of digital technologies on resilience in the agri-food supply chain. This study confirms the critical role of resilience in the agri-food supply chain and the significance of digital technologies in improving supply chain resilience and firm performance. The study also suggests that a firm should proactively build its resilience capability rather than learn from past disruptions. The findings are useful for academics and practitioners alike, in the acknowledgment of the significant effects of digital technologies on supply chain resilience in the agri-food industry. Some technologies are not agri-food specific but have a place in the industry, while others are tailor made for farming applications. Parties in the agri-food industry must take advantage of Industrial Revolution 4.0 and digital technologies to flourish in the agri-food industry. / Business Administration/Interdisciplinary

As end-consumers are surrounded by a tremendous number of multi-channel retailers and their products, clothing retailers are exposed to numerous clothing samples with a variety of styles in various price ranges, offered by onshore and offshore manufacturers. Although manufacturers or vendors offer well-salable products, a retail business may not be successful in maximizing profits without a strategic retail buying planning process. The purpose of this study is to develop a retail buying model for clothing retailers. In order to test the variables that comprise the retail buying model, the objectives of the study are to: (a) investigate important assortment decision factors for clothing retail buying; (b) segment clothing retail buyers by their decision factor uses; (c) characterize the segments by buyer (i.e., age, gender, education, experience, employment) and company demographics (i.e., types of products, type of store, size of the firm); (d) examine the relationship between these demographic variables and the factor uses; (e) examine the influence of the factor uses on the success of assortment planning; (f) examine the influence of the success of assortment planning on firm performance; and, (g) examine the influence of extraneous variables (i.e., retail environment) on firm performance. After two pilot tests, adjustments were made to wording in the questionnaire. Data collection, using a pen and paper questionnaire, was conducted using convenience and snowball sampling. Through this method, 425 clothing retail buyers, merchandisers, or store owners, who are involved assortment planning and buying in South Korea, participated in the survey. A variety of statistical analyses was used to test the hypotheses. For testing Hypothesis 1, the mean and standard deviation of the assortment factor items were used to rank important decision factors for assortment planning. To test Hypothesis 2, retail buyers were segmented by their assortment decision factor use through exploratory factor analysis and K-means cluster analysis. For Hypothesis 3, Chi-square was utilized to characterize the segments of buyers and merchandisers from Hypothesis 2, using buyer and company demographics. For Hypothesis 4, Pearson and Spearman Correlations were used to test if correlations exist between buyer and company demographic variables and decision factor use. For Hypotheses 5 to 7, a Structural Equation Model (SEM) was developed to test if causal relationships exist among assortment decision factor use, the success of assortment planning, firm performance, and retail environment. All Hypotheses were fully or partially supported. Based on the results of hypotheses testing, the finalized retail buying model was developed. The finalized retail buying model based on the use of assortment decision factors will benefit retailers by helping retail buyers to analyze available information and identify the need for additional decision factors. Due to the use of convenience and snowball sampling as well as the limited geographic location of the survey, the finding of the current study cannot be generalized to the general population of clothing retail buyers. Future studies using probability sampling methods, utilizing qualitative methods, and/or examining in different countries, are suggested to verify the current findings and confirm the validity of the framework. / Ph. D.

This dissertation consists of three papers related to firms' resiliency to supply chain disruptions. The first paper seeks to evaluate the effects of supply chain disruptions on firms' performance by using a recent dataset of supply chain disruptions. To this end, we analyzed operating and stock market performances of over 300 firms that experienced a supply chain disruption during 2005 to the end of 2014. The results show that supply chain disruptions are still associated with a significant decrease in operating income, return on sales, return on assets, sales, and a negative performance in total assets. Supply chain disruptions are also associated with a significant negative abnormal stock return on the day of the supply chain disruption announcements. These results are in line with previous findings in the literature. In the second paper, in order to provide a more detailed characterization of negative impacts of disruptions on firms' performance, we develop three complementary measures of system loss: the initial loss due to the disruption, the maximum loss, and the total loss over time. Then, we utilize the contingent resource-based view to evaluate the moderating effects of operational slack and operational scope on the relationship between the severity of supply chain disruptions and the three complementary measures of system loss. We find that maintaining certain aspects of operational slack and broadening business scope can affect these different measures of loss in different ways, although these effects are contingent on the disruptions' severity. The third paper examines relationships between the origin of supply chain disruptions, firms' past experience, and the negative impacts of supply chain disruptions on firms' performance. This third study shows that the impact of external and internal supply chain disruptions on firms' performance can be different when firms do and do not have past experience with similar events. For example, the results show that past experience significantly decreases initial loss, recovery time, and total loss over time experienced by firms after internal disruptions, although past experience may not decrease initial loss, recovery time, and total loss over time in the case of external disruptions. / Ph. D.

No / We analyse the impact of ownership and corporate control on firms’ investment using the 2001survey of Yacoub et al. on Ukrainian firms. The model explains investment by output, financial and soft budget constraints, and corporate control (and ownership) categories potentially enjoying private benefits of control. We find that the corporate control model fits better than the ownership model,a negative relationship between state and employee control and firms’ investment, and evidence forthe presence of soft budget constraints. A negative relationship between firms’ investment and the relative size of non-monetary transactions strengthens the conclusion of private benefits of control impacting investment.

Yes / This article reviews the literature on human capital resources and develops a conceptual model incorporating social capital, relational capital and knowledge as the components of human capital resources and linking these to competitive advantage. Scholars from various disciplines expanded our understanding of human capital as important organizational resources but research in this field remains fragmented. Building on past research this review contributes to existing knowledge in human capital resources by introducing an integrated conceptual framework comprising of both micro-level human capital and macro-level strategic human capital resources. In so doing it provides alternative definitions for human capital resources with the aim to make their assessment and understandability more meaningful and clearer than what has been offered so far. Moreover, by bringing knowledge, social capital and relational capital under human capital, this review encourages a dialogue among scholars from various disciplines to investigate the creation and accumulation of strategic human capital resources holistically.

Yes / This study examines the effects of firm performance and corporate governance on chief executive officer (CEO) compensation in an emerging market, Pakistan. Using a more robust Generalized Method of Moments (GMM) estimation approach for a sample of non-financial firms listed at Karachi Stock Exchange (KSE) over the period 2005 to 2012, we find that both current and previous year accounting performance has positive influence on CEO compensation. However, stock market performance does not appear to have a positive impact on executive compensation. We further find that ownership concentration is positively related with CEO compensation, indicating some kind of collusion between management and largest shareholder to get personal benefits. Inconsistent with agency theory, CEO duality appears to have a negative influence, while board size and board independence have no convincing relationship with CEO compensation, indicating board ineffectiveness in reducing CEO entrenchment. The results of dynamic GMM model suggest that CEO pay is highly persistent and takes time to adjust to long-run equilibrium.

Yes / Achieving energy efficiency through adoption of energy management practices remain top priorities among industry. Studies focusing on energy management practices are scarce and this area needs to be focused. Building on the perspective of resource-based view and behavioral theory of corporate governance, the purpose of the study is to develop and test an integrative framework linking manufacturing firm's energy management practices (EMPs) to environmental and financial performance through mediating roles played by energy efficiency and audit. The moderating role played by the top management commitment is further examined. Structural equation modeling was employed to test the hypotheses alongside Hayes' PROCESS to check moderation effects. Results from a survey of 637 employees working in Small- and Medium-sized Enterprises (SMEs) of Indian manufacturing firms indicate that EMPs result into increased environmental as well as financial performance of the firm. It was also found that energy efficiency mediates the relationship between the adoption of EMPs and environmental performance, amplified by top management commitment. Further, energy audit mediates the effect of EMPs on energy efficiency. The study contributes to offering the new research directions to identify alternatives that monetises environmental concepts such as energy efficiency, leading to higher performance of SMEs. / The full-text of this article will be released for public view at the end of the publisher embargo on 20 Dec 2022.

Yes / Cutting-edge technologies like big data analytics (BDA), artificial intelligence (AI), quantum computing, blockchain, and digital twins have a profound impact on the sustainability of the production system. In addition, it is argued that turbulence in technology could negatively impact the adoption of these technologies and adversely impact the sustainability of the production system of the firm. The present study has demonstrated that the role of technological turbulence as a moderator could impact the relationships between the sustainability the of production system with its predictors. The study further analyses the mediating role of operational sustainability which could impact the firm performance. A theoretical model has been developed that is underpinned by dynamic capability view (DCV) theory and firm absorptive capacity theory. This model was verified by PLS-SEM with 412 responses from various manufacturing firms in India. There exists a positive and significant influence of AI and other cutting-edge technologies for keeping the production system sustainable.

Yes / Despite the importance of firms' strategy in corporate sustainability (CS), insufficient research has focused on the role of business strategy in the relationship between CS and firm performance. Focusing on generic business strategy, this study examines when and under what conditions CS relates to firm performance. The main argument is that the effects of CS on firm performance are contingent on the firm's business strategy. The findings present that CS strengths are positively related to firm performance when firms pursue a differentiation strategy. Meanwhile, CS concerns are negatively associated with firm performance when firms operate with a differentiation strategy. Empirical evidence is obtained from a sample of U.S. firms and fixed effects panel regression models, which controls for unobservable time-invariant factors that are correlated with covariates. This study contributes to the literature on CS and firm performance by suggesting business strategy as an important moderating condition in the CS-firm performance link.

Yes / In today’s rapidly changing business landscape, organizations increasingly invest in different technologies to enhance their innovation capabilities. Among the technological investment, a notable development is the applications of big data analytics (BDA), which plays a pivotal role in supporting firms’ decision-making processes. Big data technologies are important factors that could help both exploratory and exploitative innovation, which could affect the efforts to combat climate change and ease the shift to green energy. However, studies that comprehensively examine BDA’s impact on innovation capability and technological cycle remain scarce. This study therefore investigates the impact of BDA on innovation capability, technological cycle, and firm performance. It develops a conceptual model, validated using CB-SEM, through responses from 356 firms. It is found that both innovation capability and firm performance are significantly influenced by big data technology. This study highlights that BDA helps to address the pressing challenges of climate change mitigation and the transition to cleaner and more sustainable energy sources. However, our results are based on managerial perceptions in a single country. To enhance generalizability, future studies could employ a more objective approach and explore different contexts. Multidimensional constructs, moderating factors, and rival models could also be considered in future studies.