A multi-attribute data mining model for rule extraction and service operations benchmarking

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Purpose Customer differences and similarities play a crucial role in service operations, and service industries need to develop various strategies for different customer types. This study aims to understand the behavioral pattern of customers in the banking industry by proposing a hybrid data mining approach with rule extraction and service operation benchmarking. Design/methodology/approach The authors analyze customer data to identify the best customers using a modified recency, frequency and monetary (RFM) model and K-means clustering. The number of clusters is determined with a two-step K-means quality analysis based on the Silhouette, Davies–Bouldin and Calinski–Harabasz indices and the evaluation based on distance from average solution (EDAS). The best–worst method (BWM) and the total area based on orthogonal vectors (TAOV) are used next to sort the clusters. Finally, the associative rules and the Apriori algorithm are used to derive the customers' behavior patterns. Findings As a result of implementing the proposed approach in the financial service industry, customers were segmented and ranked into six clusters by analyzing 20,000 records. Furthermore, frequent customer financial behavior patterns were recognized based on demographic characteristics and financial transactions of customers. Thus, customer types were classified as highly loyal, loyal, high-interacting, low-interacting and missing customers. Eventually, appropriate strategies for interacting with each customer type were proposed. Originality/value The authors propose a novel hybrid multi-attribute data mining approach for rule extraction and the service operations benchmarking approach by combining data mining tools with a multilayer decision-making approach. The proposed hybrid approach has been implemented in a large-scale problem in the financial services industry

Hybrid business offerings in small internationalisers: A mixed-method analysis of internal capabilities through hesitant fuzzy information

Purpose: In this research, the initial list of internal capabilities in small and medium-sized enterprises (SMEs) leading to success in international markets has been extracted. Then, the most relevant capabilities to international SMEs under servitisation and hybrid offerings have been screened. Next, the selected capabilities have been classified, and ultimately the relationship amongst the capabilities has been analysed. The conceptual model for SMEs participating in international markets with hybrid offerings has been illustrated. Design/methodology/approach: A literature review has been employed to extract the initial list of internal capabilities to address the research objectives. Then, a novel hesitant fuzzy Delphi (HFD) method has been developed to select the most relevant capabilities for SMEs for hybrid offerings in international markets by using the experts opinions. Subsequently, a novel hesitant fuzzy interpretive structural modelling (HFISM) has been developed to classify the capabilities, design a level-based conceptual model and present the relationship amongst the prominent capabilities. Findings: After the literature review, sixteen internal capabilities leading to success in the international market via hybrid offerings have been extracted. Then, eight selected capabilities were chosen for further investigation by applying 15 expert opinions and via the HFD approach. According to HFISM results, a level-based conceptual model was emanated, and “ability to take advantage of international opportunities”, “financial strength”, “technology level” and “efficient innovation management” were considered as the most fundamental capabilities resulting in successful hybrid offerings in international markets. Originality/value: Alongside the multi-layer decision-making approach developed in this manuscript to analyse the internal capabilities roles in hybrid offering success towards international markets, to the best knowledge of the authors, the hesitant fuzzy approaches developed in this article have not been previously presented by any other scholar. A novel HFD approach has been designed for consensus amongst the experts under uncertain circumstances. Furthermore, a novel HFISM has been suggested and employed in this research to comprehend the relationship amongst the internal capabilities

Optimal strategic alliance in multi‐echelon supply chains with open innovation

The author's final peer reviewed version can be found by following the URI link. The Publisher's final version can be found by following the DOI link.We propose a game‐theoretic approach to examine several possible coalition strategies in a four‐echelon supply chain consisting of a supplier, manufacturer, wholesaler, and retailer. A solitude model is used to probe the role of learning in quality improvements, and experimental design is conducted to evaluate all possible supply chain coalition strategies between echelons. The novelty of this study is the comprehensive evaluation of knowledge‐sharing strategies in collaborative supply chains. The results confirm that the Delta model with a coalition among a supplier, manufacturer, and retailer is the best strategy

Developing sustainable competitive advantages from the lens of resource-based view:evidence from IT sector of an emerging economy

The present study examines the IT industry’s sustainable competitive advantages (CAs) from a resource-based view (RBV). Therefore, a list of CAs in three areas of the triple bottom line (TBL), including economic, social, and environmental, are extracted by thoroughly studying the relevant literature. These attributes are then evaluated by small and medium enterprises (SMEs) managers in the IT sector by implementing a Multi-level hybrid Decision-Making approach. This step employs a modified Delphi technique combined with linguistic z-numbers. Further, by reviewing the literature, the list of intangible resources is counted, and the importance of these resources is measured via the linguistic z-number BWM (Best Worst Method). Finally, the degree of the controllability of critical CAs is prioritised by z-number TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and then classified found on the resources. Consequently, different classes are discussed, and appropriate strategies for dealing with each are presented

Differential game approach to pricing and advertising decisions

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.This study proposes a model to make concurrent decisions on dynamic pricing and advertising to maximise firms' profitability over an infinite time horizon in a duopoly market. To this end, the Nerlove-Arrow pricing and advertising model is designed in the presence of shifting costs in a dynamic duopolistic competition as a differential game. The Nash equilibrium solution is defined based upon a set of Hamilton–Jacobi–Bellman. Four scenarios are applied for economic interpretations and the efficacy of the model