scholarly journals Sustainable partner selection for collaborative networked organisations with risk consideration in the context of COVID-19

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yvonne Badulescu ◽  
Ari-Pekka Hameri ◽  
Naoufel Cheikhrouhou

Purpose Collaborative networked organisations (CNO) are a means of ensuring longevity and business continuity in the face of a global crisis such as COVID-19. This paper aims to present a multi-criteria decision-making method for sustainable partner selection based on the three sustainability pillars and risk. Design/methodology/approach A combined analytic hierarchy process (AHP) and fuzzy AHP (F-AHP) with Technique for Order of Preference by Similarity to Ideal Solution approach is the methodology used to evaluate and rank potential partners based on known conditions and predicted conditions at a future time based on uncertainty to support sustainable partner selection. Findings It is integral to include risk criteria as an addition to the three sustainability pillars: economic, environmental and social, to build a robust and sustainable CNO. One must combine the AHP and F-AHP weightings to ensure the most appropriate sustainable partner selection for the current as well as predicted future period. Research limitations/implications The approach proposed in this paper is intended to support existing CNO, as well as individual firms wanting to create a CNO, to build a more robust and sustainable partner selection process in the context of a force majeure such as COVID-19. Originality/value This paper presents a novel approach to the partner selection process for a sustainable CNO under current known conditions and future uncertain conditions, highlighting the risk of a force majeure occurring such as COVID-19.

Kybernetes ◽  
2015 ◽  
Vol 44 (10) ◽  
pp. 1504-1522 ◽  
Author(s):  
Soe Tsyr Yuan ◽  
Pei Hung Hsieh ◽  
Yu-Chen Yeh

Purpose – In the service economy era, service value is created from the evaluation of customer experience and it is important to study alliance partner selection for improving service provision. Nevertheless, most of the existing alliance partner selection approaches concentrate on the functional aspects. The purpose of this paper is to provide a novel approach that is customer-centric and emphasizes the emotional aspect of service value. Design/methodology/approach – This paper presents a metaphor-based alliance partner recommendation mechanism (MAPRM) that employs the computing metaphor approach to recommend alliance partners for companies in an innovative way. The main ideas of metaphors are the comparison made between two unlike things that actually have something in common so as to attain innovative thinking. Findings – This study uses the scenario of regional tourism innovation to demonstrate the attempted contributions of MAPRM. The simulation evaluation results show that MAPRM can utilize knowledge and resources from companies to achieve specific alliance goals of satisfying desired customer experiences represented by images that can be analyzed and created based on customers’ feedback and their interactions with companies. Originality/value – MAPRM aims to assist companies to find appropriate alliance partners which offer potential innovation opportunities for service value provision. It is capable of facilitating the alliance partner selection process and assessing customers’ needs at the same time.


2018 ◽  
Vol 25 (6) ◽  
pp. 1844-1863 ◽  
Author(s):  
Kunal Ganguly ◽  
Siddharth Shankar Rai

Purpose To enhance the transparency of the supply chain and ensure proper dissemination of information among the supply chain members in a timely manner, more and more companies are implementing supply chain information system (SCIS). Often the challenge among the organizations is how to go for a proper SCIS implementation and to identify the key performance indicators (KPIs) to evaluate the SCIS. The purpose of this paper is to provide a framework to evaluate the KPIs for SCIS of SCISs implementation from user’s perspectives. Design/methodology/approach In this paper, 16 KPIs were identified based on extensive literature survey. A fuzzy analytic hierarchy process (AHP) model is constructed to measure the users’ perceived importance and satisfaction for the KPIs. Subsequently, based on these two measurements, an importance-performance analysis (IPA) model along with a customer satisfaction attitude (SA) index is developed to categorize and prioritize the KPIs. As an empirical study, SCIS users across five industries belonging to different sectors were investigated to validate the model. Findings An IPA model along with a customer SA index is developed based on a fuzzy AHP model to evaluate the KPIs and provide the priorities of their improvement. Based on this result, some management implications and suggestions are proposed. Research limitations/implications The study was limited to five organizations. More representative samples which can be sector specific can ensure better confirmation of the empirical results. Originality/value The KPIs identified in the research indicate the nature and dynamics of a complex SCIS implementation. It can serve as a checklist of areas that require attention when implementing a SCIS. The KPIs are presented through grouping in a systemic way. The development of the SAs in IPA model using fuzzy AHP is a novel approach.


2015 ◽  
Vol 22 (6) ◽  
pp. 1158-1174 ◽  
Author(s):  
Vinod Yadav ◽  
Milind Kumar Sharma

Purpose – The purpose of this paper is to propose a multi-criteria supplier selection model using fuzzy analytical hierarchy process (FAHP) approach for a leading automobile company in India. Design/methodology/approach – FAHP approach followed by a sensitivity analysis has been used. Findings – In this study, a FAHP-based supplier selection model is proposed to provide useful insights in choosing appropriate suppliers in dynamic situations in order to enhance long-term relationship with them. Practical implications – This study proposes a supplier selection model for an automobile industry which often faces heterogeneous supply environments. This model may have a high acceptability where a large number of suppliers are available to supply the materials or provide the services. As analytic hierarchy process is the most widely used methodology for supplier selection, however, it becomes less efficient in case of inconsistencies observed in the data. However a FAHP-based approach may overcome this difficulty. Originality/value – It contributes to supplier selection process and points out the importance of supplier selection problem, especially in the context of multi-criteria decision-making in Indian scenario.


2015 ◽  
Vol 17 (1) ◽  
pp. 23-35 ◽  
Author(s):  
João Alves ◽  
Raquel Meneses

Purpose – This paper aims to contribute towards a better understanding of the partner selection process, which anticipates a successful co-opetition partnership. Co-opetition partnerships refer to developing cooperation efforts between competitors. The scarcity of studies conducted in this field to date provides limited contribution for the understanding of the partner selection process in this, particularly, paradoxical concept. Design/methodology/approach – This study follows a methodology based on systematic combining for the qualitative analysis of four cases of domestic co-opetition in Portugal. A sample range of eight companies was selected for a series of semi-structured interviews. Testimonials were transcribed and data coded for content analysis. Findings – Results indicate that prior personal relationships between decision-makers are facilitators for the implementation of cooperation partnerships with competitors. Based on these findings, this paper proposes a three-step model to explain the process of partner selection for co-opetition partnerships. According to this model, after opting to commence a new coopetitive business alliance, the manager undergoes a first unconscious selection based on his/her own prior personal relationships, followed by a conscious and judicious selection based on specific criteria related to partner’s operational skills, resources, effectiveness and trust. Research limitations/implications – Given that the sample is entirely formed by companies from one single country, further research would benefit from the inclusion of other countries expressing different business contexts and cultural environments. Originality/value – The value of paper derives from the comprehensive realization of partner selection for domestic co-opetition as fundamentally a network-related process.


2021 ◽  
pp. 1-11
Author(s):  
Aysu Melis Buyuk ◽  
Gul T. Temur

In line with the increase in consciousness on sustainability in today’s global world, great emphasis has been attached to food waste management. Food waste is a complex issue to manage due to uncertainties on quality, quantity, location, and time of wastes, and it involves different decisions at many stages from seed to post-consumption. These ambiguities re-quire that some decisions should be handled in a linguistic and ambiguous environment. That forces researchers to benefit from fuzzy sets mostly utilized to deal with subjectivity that causes uncertainty. In this study, as a novel approach, the spherical fuzzy analytic hierarchy process (SFAHP) was used to select the best food treatment option. In the model, four main criteria (infrastructural, governmental, economic, and environmental) and their thirteen sub-criteria are considered. A real case is conducted to show how the proposed model can be used to assess four food waste treatment options (composting, anaerobic digestion, landfilling, and incineration). Also, a sensitivity analysis is generated to check whether the evaluations on the main criteria can change the results or not. The proposed model aims to create a subsidiary tool for decision makers in relevant companies and institutions.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anchal Gupta ◽  
Rajesh Kr Singh ◽  
Shivam Gupta

PurposeThe purpose of this study is to identify factors that are important for logistics organizations from the perspective of manpower readiness for digitization of logistics operations. The study also prioritizes the identified factors and also evaluates the readiness index of manpower for the digitalization of logistics processes.Design/methodology/approachThe factors for manpower readiness are identified through literature review and analysis of a case study. Three major categories of factors are identified. These are organizational, behavioural and technological factors. Under these three major categories of factors, 18 sub-factors are identified. Thereafter, with experts' inputs, the factors are prioritized using Fuzzy analytic hierarchy process (AHP). Further, a case illustration of an Indian logistics company has been taken to understand the current processes, technical capabilities, manpower skills and organization culture. After the case analysis and expert inputs, the manpower readiness index has been evaluated by using graph theory matrix approach (GTMA).FindingsThe prioritization of manpower readiness factors has been done using Fuzzy AHP. Organizational factors are found to be the most important factors which require quick attention. Sub-factors that are most important for building competencies in the logistics sector are providing the right training on functional skill development (0.129), top management support and commitment for digitalization (0.117), and organizational culture for process digitalization (0.114), etc. Finally, framework for evaluation of manpower readiness index for logistics operations in the digital age has been illustrated for a case company.Practical implicationsIndian logistics companies can benchmark their readiness index with respect to the best in the industry. Based on the readiness index, logistics companies can analyse their position, gaps from best and worst and can also identify potential areas for improvement.Originality/valueThe novelty of the study lies in the development of a framework for manpower readiness for digitalization in the logistics sector. In literature, this field is very less researched and provides the scope for developing strategies for improving manpower competencies for Industry 4.0. Logistics companies can improve their performance by making their manpower ready based on results obtained for readiness index.


2018 ◽  
Vol 25 (5) ◽  
pp. 1528-1547 ◽  
Author(s):  
Anil Kumar ◽  
Amit Pal ◽  
Ashwani Vohra ◽  
Sachin Gupta ◽  
Suryakant Manchanda ◽  
...  

Purpose Supplier selection for capital procurement is a major strategic decision for any automobile company. The decision determines the success of the company and must be taken systematically with the utmost transparency. The purpose of this paper is to construct capital procurement decision-making model to optimize supplier selection in the Indian automobile industry. Design/methodology/approach To achieve the stated objective, a combined approach of fuzzy theory and AHP-DEMATEL is applied. Evaluation parameters are identified through an extensive literature review and criteria validation has been introduced through a Fuzzy Delphi method by using fuzzy linguistic scales to handle the vagueness of information. AHP is employed to find the priority weight of criteria, although an inter-relationship map among criteria is not possible through AHP alone since it considers all criteria as independent. To overcome this, DEMATEL is used to establish cause-effect relationships among criteria. Findings The results show that the total cost of ownership (TOC) is the first weighted criterion in supplier selection for capital procurement, followed by manufacturing flexibility and maintainability, then conformity with requirement. The cause-effect model shows that supplier profile, TOC, service support and conformity with requirement are in the cause group and are considered to be the most critical factors in selecting the supplier. Originality/value The study’s outcome can help the automobile industry to optimize their selection process in selecting their suppliers for capital procurement; the proposed model can provide guidelines and direction in this regard.


2021 ◽  
Vol 18 (1) ◽  
pp. 34-57
Author(s):  
Weifeng Pan ◽  
Xinxin Xu ◽  
Hua Ming ◽  
Carl K. Chang

Mashup technology has become a promising way to develop and deliver applications on the web. Automatically organizing Mashups into functionally similar clusters helps improve the performance of Mashup discovery. Although there are many approaches aiming to cluster Mashups, they solely focus on utilizing semantic similarities to guide the Mashup clustering process and are unable to utilize both the structural and semantic information in Mashup profiles. In this paper, a novel approach to cluster Mashups into groups is proposed, which integrates structural similarity and semantic similarity using fuzzy AHP (fuzzy analytic hierarchy process). The structural similarity is computed from usage histories between Mashups and Web APIs using SimRank algorithm. The semantic similarity is computed from the descriptions and tags of Mashups using LDA (latent dirichlet allocation). A clustering algorithm based on the genetic algorithm is employed to cluster Mashups. Comprehensive experiments are performed on a real data set collected from ProgrammableWeb. The results show the effectiveness of the approach when compared with two kinds of conventional approaches.


2019 ◽  
Vol 32 (5) ◽  
pp. 1039-1057
Author(s):  
Kunal Ganguly

Purpose The purpose of this paper is to present a comprehensive framework for quality-related performance measures linked to supply chain risk (SCR) by analyzing and framing them into a hierarchical structure. Design/methodology/approach In this paper, quality-related performance measures (QM) are identified on the basis of literature survey and expert opinion. The quality measures are formulated as hierarchy structure and fuzzy AHP as a multi attribute decision-making tool is applied to judge the viable candidates. Findings Based on a fuzzy AHP approach, a revised risk matrix with a continuous scale was proposed to assess the QMs’ classes. The result classifies the QMs in different categories (extreme, high, medium and low). Based on this result, some management implications and suggestions are proposed. Originality/value The present work proposes an assessment methodology for quality-related performance measures linked to SCR. The revised risk matrix with continuous scale for risk assessment in this field is a novel approach. This study contributes to the supply chain management and quality management literature, and provides suggestions for managers to adopt different strategies for different risk classes.


2020 ◽  
Vol 13 (12) ◽  
pp. 3747-3765
Author(s):  
Rahmi Baki

Purpose The purpose of this study is to develop a useful, effective and comprehensive approach to facilitate the evaluation of hotel websites. Design/methodology/approach The paper examines the literature evaluating e-commerce sites, particularly that is focused on hotel, tourism and travel. Moreover, 5 criteria and 19 sub-criteria are identified, and a two-step method is proposed for the assessment of hotel websites whereby the global weights of the proposed criteria are determined by the fuzzy analytic hierarchy process, and hotel websites are ranked through the fuzzy technique for order preference by similarity to ideal situation. Findings The results show that the leading criteria to effectively evaluate hotel websites are trust and information quality and that the most important sub-criteria are special discounts, assurance and reservation information. Practical implications This research offers practical advice to increase understanding of the determinants of an effective hotel website so that appropriate strategies can be developed to convert a website visitor into a customer. Originality/value The study aims to contribute to businesses operating in the tourism sector which seeks to increase the effectiveness of their websites by identifying criteria and proposing a methodology for hotel website evaluation.


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