Supply chain management is described as a business strategy that provides operative management of financial, material, and other information flows to ensure harmonization in distributed organizational structures. The predefined aim of this study was to describe the effects of green supply chain management practices on competitive strategic alliances using automobile firms in China. The study aimed to demonstrate different factors that aid strategic alliances, which automobile firms must acknowledge to improve their performance. Fifty automobile firms were used as the study population. The respondents were senior managers of five active areas in each automobile firm. There were a total of 420 respondents, among whom 320 respondents were selected by the convenience sampling method. The study was quantitative, while the data source was primary; the data were obtained using a closed-ended questionnaire as the major instrument for data collection. This closed-ended questionnaire was sent to the intended respondents via email and WeChat simultaneously. Five active areas were included, and Cronbach’s alpha values were measured for each area. The values obtained ranged from 0.8 to 0.9, revealing the data’s consistency and reliability. The primary data obtained were analyzed using descriptive statistics for demographic data and inferential structural equation modeling (SEM) for multivariate data. Considering the outcomes of the research analysis, it was concluded that forming competitive strategic alliances in firms to manage green supply chains could bring several benefits.

The purpose of the research was to evaluate the competitive strategies of the two big companies in Pakistan. To achieve this aim, the two competing companies in the ice cream sector were evaluated that include Unilever Pakistan and Engro for their brands Magnum and Omore respectively. The primary research was conducted using a questionnaire survey as the research instrument. The instrument was evaluated for its reliability and then the research was conducted with 100 consumers. The findings were relevant to the literature discussed in the research that the product is differentiated by adding value to add. Additionally, it was also found that to create value it is not limited to add value through quality, but it can also be differentiated by adding features into the product to add value. Nevertheless, the findings from the study revealed that the consumers in Pakistan prefer the differentiated product. Particularly, the consumers preferred Magnum ice cream over Cornetto and Omore because it was rich in taste and quality. Although, consumers also regarded it as expensive but they also responded to a survey that it offers value for the price. Notably, the consumers were also found preferring a low-cost product which indicates that in Pakistan the competitive strategy that is successful is differentiation and that Unilever Pakistan capitalizes with differentiation through Magnum and also serves lowcost markets and competes with OMORE brand. The recommendations were proposed for further research.

Based on the resource-based theory, the current study examines the relationship between competitive strategies and strategic alliance performance. Furthermore, big data predictive analytics is treated as a boundary condition between competitive strategies and strategic alliance performance. Big data of predictive analytics in operations and industrial management has been a focal point in the current era. There has been little attention has about big data predictive analytics influences on competitive strategies and strategic alliance performance, especially in developing countries like Pakistan. A survey instrument was used to record the responses from 331 employees of the telecom sectors companies working in Pakistan. Study findings show that big competitive strategies have a positive and significant relationship with strategic alliances performance. It was also found that big data predictive analytics plays the role of moderator between competitive strategies and strategic alliance performance. The study add a new perspective and contribution to the literature on big data predictive analytics, strategic alliance performance, and competitive strategies in Pakistan's telecom sector companies. Further, the study results explain that big data analytics is just like the companies' lifeblood in the current era. The efficient and effective use of big data analytics, companies can boost their standards in a competitive environment.

The study is based on the notion that big data predictive analytics is important for developing strategic alliances performance of companies. this study investigates the relationship between big data predictive analytics, big data culture, and competitive strategies 'techniques were adopted, such as descriptive statistics, correlation,regression, etc. using SPSS and SmartPLS statistical software. Hypotheses were tested with bootstrapped analysis using SEM (through SmartPLS). The study developed a structural equation model by using the SEM analysis. The results of the SEM analysis suggested the hypothesized model of the study was valid. The results supported all the hypotheses of the study.Through empirical analysis, demonstrated the conclusion is that the big data predictive analytics has a positive and significant relationship with strategic alliance performance