Search results

This study integrates economic/ecology (eco)-attributes and performance to build a sustainable service supply chain management (SSCM) model.

This study proposes the use of the fuzzy Delphi method to screen for the less important attributes and applies a network data envelopment analysis to explore the hierarchical and eco-efficient network interrelationships. The causality and hierarchal eco-efficient model is acquired using a fuzzy decision-making trial and evaluation laboratory analysis

The findings are as follows: (1) the information and technology management process is derived by enhancing sustainable customer and supplier relationship management, and (2) the eco-efficient model is improved based on long-term relationships with suppliers – that is, synergistic suppliers improve the service chain quality and provide services in an appropriate and timely manner – and research and development coordination. The theoretical and managerial implications are discussed.

The eco-efficient model reveals that the sustainable customer relationship management process, sustainable supplier relationship management process and information and technology management process are the major causal attributes in the model.

The eco-efficient model must be based on (1) long-term relationships with suppliers, (2) synergistic suppliers to improve service chain quality, (3) the provision of services in a timely manner and (4) research and development coordination.

Prior studies neglect to build an ecological economy model using the efficiency causality model of hierarchical interrelationships. Traditional SSCM fails to involve the triple bottom line performance toward sustainability.

To provide an interesting approach for determining interval measures, through the analytic hierarchy process, for integration with social network analysis for knowledge mapping in organizations.

In order to develop improved organizational and business processes through knowledge management, a knowledge audit should be conducted to better understand the knowledge flows in the organization. An important technique to visualize these knowledge flows is the use of a knowledge map. Social network analysis can be applied to develop this knowledge map. Interval measures should be used in the social network analysis in order to determine the strength of the connections between individuals or departments in the organization. This paper applies the analytic hierarchy process to develop these interval measures, and integrates the values within the social network analysis to produce a meaningful knowledge map.

The analytic hierarchy process, when coupled with social network analysis, can be a useful technique for developing interval measures for knowledge‐mapping purposes.

The analytic hierarchy process may become tedious and arduous for use in large social network maps. More research needs to be conducted in this area for scalability.

As social network analysis is gaining more prominence in the knowledge management community, the analytic hierarchy process may be able to provide more valuable measures to determine the strengths of relationships between actors than simply using ordinal numbers.

Coupling the analytic hierarchy process with social network analysis provides a novel approach for future knowledge‐mapping activities.

The paper provides an overview of research published in the innovation and operations management (IOM) literature on 15 methods for cost management in new product development, and it provides a comparison to an earlier review of the management accounting (MA) literature (Wouters & Morales, 2014).

This structured literature search covers papers published in 23 journals in IOM in the period 1990–2014.

The search yielded a sample of 208 unique papers with 275 results (one paper could refer to multiple cost management methods). The top 3 methods are modular design, component commonality, and product platforms, with 115 results (42%) together. In the MA literature, these three methods accounted for 29%, but target costing was the most researched cost management method by far (26%). Simulation is the most frequently used research method in the IOM literature, whereas this was averagely used in the MA literature; qualitative studies were the most frequently used research method in the MA literature, whereas this was averagely used in the IOM literature. We found a lot of papers presenting practical approaches or decision models as a further development of a particular cost management method, which is a clear difference from the MA literature.

This review focused on the same cost management methods, and future research could also consider other cost management methods which are likely to be more important in the IOM literature compared to the MA literature. Future research could also investigate innovative cost management practices in more detail through longitudinal case studies.

This review of research on methods for cost management published outside the MA literature provides an overview for MA researchers. It highlights key differences between both literatures in their research of the same cost management methods.

Supply chain security has been recognized as an important part of managing business risks. The purpose of this paper is to propose a methodology with systematic metrics for logistics service providers (LSPs) to develop their security design to meet customer demands.

The study is based on a three-stage process of desk research, content validation test, and in-depth case study. The study demonstrates an integrated analytical approach which combines analytical network process (ANP) with quality function deployment (QFD), and then applies the approach to an international LSP.

A case study of an international LSP shows how the ANP-QFD approach can be deployed to understand customers’ expectation for security and develop tactics and measures with the aim to achieve the desirable outcome for LSPs’ security design.

The paper contributes to supply chain security literature and practice. This study is among the research taking the first step to use ANP-QFD to translate the customer requirements (CRs) for supply chain security into systematic metrics for LSPs to develop their security design. Results from such research into the development of security performance can benefit LSPs in terms of increasing the effectiveness and improving the customer orientation of security efforts. By extension, other firms can enhance their security design by referring to the case study and the integrated analytical method. The flexibility of this ANP-QFD approach offers leeway for firms to change the CRs and design requirements based on their unique circumstances.

The purpose of this paper is to present the development of a methodology to evaluate suppliers using portfolio analysis based on the analytical network process (ANP) and environmental factors.

The authors develop a three‐step process, first by evaluating influence/power and performance scores of suppliers using ANP. They include environmental dimensions in this analysis, then map these suppliers onto a portfolio grid. Recommendations are also made on how to manage suppliers depending on what part of the portfolio they appear based on the scores.

The technique is useful and versatile. The paper clearly discerns various characteristics of the suppliers and produced recommendations on supplier management for an exemplary case scenario.

The technique was applied for an illustrative example. Validation and application in a real world setting is required. There are many additional opportunities to further integrate other modeling tools into this process.

Managers can use this technique to help them more effectively deal with suppliers. The portfolio is a good tool for operational and strategic management of suppliers.

This tool is the first to apply ANP to supplier portfolio analysis. It is also the first tool to integrate and apply the portfolio supplier management approach to an environmentally oriented decision environment.

The purpose of this paper is to identify the barriers of knowledge management (KM) implementation in Alborz Province industrial Parks Corporation and prioritize them using fuzzy analytical network process (FANP).

Through an in-depth review of the literature on KM and researcher findings from observations and interviews with experts, the main barriers of KM implementation, namely, organizational culture, organizational structure, human resource, technology and miscellaneous factors along with their related factors in the surveyed organization were identified. Then, based on the information gathered, an expert questionnaire was developed. Finally, the priority of each main barrier and their sub-factors were determined using FANP.

The results show that human resource and organizational culture factors with the weights of 0.66 and 0.22, respectively, have the highest ranking and therefore are the most important barriers. The technology factor with the weight of 0.00002 is the least important barrier in implementing KM in the surveyed corporation.

One of the limitations of this study is the generalizability of the findings, which may be limited by the single case study method used.

There are fewer studies about KM barriers specifically with a focus on prioritizing them in organizations, especially in the context of Iran as a developing country. This study develops a comprehensive and solid mathematical technique to prioritize the identified barriers of KM implementation in the context of Iran.

There has been an increasing amount of research on personnel selection in many business disciplines (Hough & Oswald, 2000; Breaugh & Starke, 2000). Research on internal auditor selection, however, has had limited exposure in the auditing literature (Bailey, Gramling, & Ramamoorti, 2003). Recently, Seol and Sarkis (2005) introduced an analytic hierarchy process (AHP) model that used a decision hierarchy based on the CFIA (competency framework for internal auditing) framework. A limitation of AHP, however, is the assumption of strict hierarchical relationship that needs to exist among factors.

The purpose of this paper is an introduction of a more robust model, the analytical network process (ANP), which relaxes the strict hierarchical and decomposition levels of the hierarchy and incorporates possible interrelationships and interdependencies of various personnel selection criteria, factors, and alternatives. In illustrating the application, we return to the CFIA model framework, describe how and where interdependencies exist amongst the CFIA factors/attributes, and how ANP is used in the internal auditor selection process. The illustration will also describe some sensitivity analysis for the ANP approach. The tool is not without its limitations that include the potential for geometrically more questions and information elicitation from the decision makers. Finally managerial and research implications associated with the technique and results are described.

In the past decades, artificial intelligence (AI)-based hybrid methods have been increasingly applied in construction risk management practices. The purpose of this paper is to review and compile the current AI methods used for cost-risk assessment in the construction management domain in order to capture complexity and risk interdependencies under high uncertainty.

This paper makes a content analysis, based on a comprehensive literature review of articles published in high-quality journals from the years 2008 to 2018. Fuzzy hybrid methods, such as fuzzy-analytical network processing, fuzzy-artificial neural network and fuzzy-simulation, have been widely used and dominated in the literature due to their ability to measure the complexity and uncertainty of the system.

The findings of this review article suggest that due to the limitation of subjective risk data and complex computation, the applications of these AI methods are limited in order to address cost overrun issues under high uncertainty. It is suggested that a hybrid approach of fuzzy logic and extended form of Bayesian belief network (BBN) can be applied in cost-risk assessment to better capture complexity-risk interdependencies under uncertainty.

This study only focuses on the subjective risk assessment methods applied in construction management to overcome cost overrun problem. Therefore, future research can be extended to interpret the input data required to deal with uncertainties, rather than relying solely on subjective judgments in risk assessment analysis.

These results may assist in the management of cost overrun while addressing complexity and uncertainty to avoid chaos in a project. In addition, project managers, experts and practitioners should address the interrelationship between key complexity and risk factors in order to plan risk impact on project cost. The proposed hybrid method of fuzzy logic and BBN can better support the management implications in recent construction risk management practice.

This study addresses the applications of AI-based methods in complex construction projects. A proposed hybrid approach could better address the complexity-risk interdependencies which increase cost uncertainty in project.

This paper aims to provide a practical model usable by organizations to help form agile virtual enterprises. The model helps to integrate a variety of factors, tangible and intangible, strategic and operational, for decision‐making purposes.

A comprehensive development of factors is determined from the literature and an analytical network process (ANP) methodology is introduced for decision model development. An illustrative example is presented.

The results provide a robust model that will aid decision makers and agile virtual enterprise brokers form partnerships within these organizational structures.

The paper introduces a conceptual model with an illustrative validating example. A practical application and reapplication of the model are required to further validate the model. ANP can require significant managerial input for its application, potentially causing fatigue for decision makers.

Practical implications include a partner selection tool and framework for decision makers. The model may be easily tweaked by the elimination or addition of decision factors and their relationships.

The paper is useful to practitioners and organizations seeking to manage partnership formation of agile virtual enterprises, an emerging organizational form. This work expands the number of factors and interrelationships among these factors that no other model has explicitly addressed for the agile virtual enterprise formation situation.

This study aims to investigate the effects of organizational culture factors on the selection of software process development models and develops a conceptual model for selecting and adopting process development models with an organizational culture approach, using 12 criteria and their sub-criteria defined in Fey and Denison’s model (12 criteria).

The research hypotheses were investigated using statistical analysis, and then the criteria and sub-criteria were selected based on Fey and Denison’s model and the experts’ viewpoints. Afterward, the organizational culture of the selected company was measured using the data from 2016 and 2017, based on Fey and Denison’s questionnaire. Due to the correlation between the criteria, using the decision-making trial and evaluation technique, the correlation between sub-criteria were determined, and by analytical network process method and using Super-Decision software, the process development model was preferred to the 12 common models in information systems development.

Results indicated a significant and positive effect of organizational culture factors (except the core values factor) on the selection of development models. Also, by changing the value of organizational culture, the selected process development model changed either. Sensitivity analysis performed on the sub-criteria implied that by changing and improving some sub-criteria, the organization will be ready and willing to use the agile or risk-based models such as spiral and win-win models. Concerning units where the mentioned indicators were at moderate and low limits, models such as waterfall, V-shaped and incremental worked more appropriately.

While many studies were performed in comparing development models and investigating their strengths and weaknesses, and the impact of organizational culture on the success of information technology projects, literature indicated that the impact of organizational sub-culture prevailing in the selection of development process models has not been investigated. In this study, new factors and indicators were addressed affecting the selection of development models with a focus on organizational culture. Correlation among the factors and indicators was also investigated and, finally, a conceptual model was proposed for proper adoption of the models and methodologies of system development.