Abstract:PurposeThe purpose of this paper is to persuade a hybrid framework, which can be used to assess the performance of various supply chains and can be further used to segregate supply chains concerning critical KPMs. The KPMs have been selected in the COVID-19 pandemic condition.Design/methodology/approachA real case of e-commerce is presented to illustrate the working of the proposed framework comprising a hybrid methodology of BWM and Fuzzy TOPSIS to measure the performance of the e-commerce supply chains by id… Show more
PurposeDespite the current progress in realizing how Big Data Analytics can considerably enhance the Sustainable Manufacturing Supply Chain (SMSC), there is a major gap in the storyline relating factors of Big Data operations in managing information and trust among several operations of SMSC. This study attempts to fill this gap by studying the key enablers of using Big Data in SMSC operations obtained from the internet of Things (IoT) devices, group behavior parameters, social networks and ecosystem framework.Design/methodology/approachAdaptive Prospects (Improving SC performance, combating counterfeits, Productivity, Transparency, Security and Safety, Asset Management and Communication) are the constructs that this research first conceptualizes, defines and then evaluates in studying Big Data Analytics based operations in SMSC considering best worst method (BWM) technique.FindingsTo begin, two situations are explored one with Big Data Analytics and the other without are addressed using empirical studies. Second, Big Data deployment in addressing MSC barriers and synergistic role in achieving the goals of SMSC is analyzed. The study identifies lesser encounters of barriers and higher benefits of big data analytics in the SMSC scenario.Research limitations/implicationsThe research outcome revealed that to handle operations efficiently a 360-degree view of suppliers, distributors and logistics providers' information and trust is essential.Practical implicationsIn the Post-COVID scenario, the supply chain practitioners may use the supply chain partner's data to develop resiliency and achieve sustainability.Originality/valueThe unique value that this study adds to the research is, it links the data, trust and sustainability aspects of the Manufacturing Supply Chain (MSC).
This research aims to select products that will be used for promotion on e-commerce platforms. The increasing use of e-commerce has led to a high level of competition in the e-commerce field. The company strives to maintain the quality of its services to increase customer satisfaction, one of which is by providing regular promotions. The process of selecting promotional products is a routine activity carried out every week. However, the current promotional product selection process is not effective enough, and there are no criteria to use as a reference for selection. This research was conducted on two e-commerce companies actively operating in Indonesia. The research began with a literature study and expert survey to select important criteria in selecting promotional products. Weighting of important criteria is carried out using the Stepwise Weight Assessment Ratio Analysis (SWARA) method. Finally, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is used to rank the best products to promote. The results showed that products from Soundcore, Lenovo, and Xiaomi were the best products with preference values of 0.83, 0.65, and 0.60 respectively.
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