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    GREEN PROCESS INNOVATION AS A MODERATOR LINKING SUSTAINABLE SUPPLY MANAGEMENT PRACTICES AND DYNAMIC CAPABILITIES WITH SUSTAINABLE PERFORMANCE IN THE MANUFACTURING SECTOR OF PAKISTAN
    (UMT.Lahore, 2022-11-04) Sobia Malik
    Innovation plays a fundamental part in sustaining a firm’s competitive advantage. Therefore, both academicians and practitioners have shown keen interest in exploring driving factors that enhance sustainable performance (SP) in firms. The literature also recognizes that the implementation of practices for sustainable supply management (SSM) fosters an organization’s sustainable performance. This study anticipates to investigate whether the adoption and implementation of SSMP and DC in firms leads to enhanced SP in developing countries like Pakistan. This empirical investigation is an effort to resolve debatable issues among scholars regarding the implementation of DC and SSM practices along with the SP relationship. This relationship is still unclear due to scholars' differing perspectives. Numerous researchers support positive relations, while some pieces of evidence show negative or no association among variables. Therefore, the focus of this study is on addressing this research gap. This study intends to empirically test the SSM practices and dimensions of the DC foster firm’s SP. The second goal of this research is to suggest a research framework for investigating green process innovation as a moderator of organizational performance. Furthermore, the moderating role of GPI with its items such as environmental, social, and economic management can affect the sustainability of a firm. A research instrument is created by combining previous measurement scales used for data collection. The scales of four items of SSMP, four dimensions of DC, and four dimensions of sustainable performance and green process innovation as a moderator are used in the research, which is adopted on a five-point Likert scale. The research design of current study is quantitative, and close-ended questions were used in the study. A deductive reasoning approach is used to obtain data from 203 respondents of almost different supply chain management departments through a survey method applying a ‘stratified’ probability sampling technique from ISO-certified manufacturing organizations in Pakistan. A survey strategy is used for the cross-sectional type of research. This data is obtained from ISO certified manufacturing organizations in Pakistan through a stratified’ probability sampling technique with 203 respondents from almost different supply chain management departments. Data would be analyzed through statistical software SPSS 26 using statistical methods to assess study hypotheses, such as correlation, descriptive statistics, and regression analysis. The proposed framework and study findings have benefited both academia and industrial practitioners. Also, it contributes to gap filling in the prevailing literature that develops understanding to address the unclear relationship between the implementation of SSM practices, DC and SP. They can consider the other variables and boundary conditions of organizational culture (OC) and digital transformation (DIT) in this association to attain improved performance results in the organizations. In previous studies, there is no research on these variables together. The findings of this study show a substantial positive association between the independent and dependent variables. To determine the abilities and skills required for the professionals of SCM to achieve better sustainable performance in their supply chain is the goal of this research. It also helps the individuals of the organizations to prepare themselves to deal with supply chain-related challenges and identify those SSM practices, which are critical to influencing a firm’s SP.
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    THE ROLE OF BIG DATA ANALYTICS IN THE FOOTWEAR SUPPLY CHAINS: A MULTIPLE CASE STUDY PERSPECTIVE
    (UMT.Lahore, 2023) FREEHA MARYUM ARSHAD
    The importance of modern information technologies; big data (BD), ERP systems, internet of things (IoT), big data analytics (BDA), and supply chain analytics (SCA) is the most important field of research for both occupations; academia and industry. To maintain sustainability in the supply chain, above mentioned technologies are the modest techniques by which firms can receive the required data on time. Which results in the integration of the supply chain process and improvement in the decision-making process. The purpose of the thesis is to analyze the importance of big data analytics and supply chain analytics for sustainable supply chain management in all types of enterprises; small- medium enterprises, and national or multinational enterprises. The importance and implementation of BDA in supply chain management have been discussed in this thesis. The previous research indicates that the application of big data analytics and supply chain analytics is the key point to establishing sustainable supply chain management. Even though there are several types of research on the implication of BDA, but still there is a gap in practical implications in organizations. For a better understanding comparison of six frameworks has been done for literature support. Further 11 interviews have been conducted with 4 organizations from the footwear industry and a proposed framework has been proposed.