Search results

The purpose of this study is to analyse various risks associated with third-party logistics (3PL) in the coffee supply chain and to present a framework that computes the influence of these risks on the critical success factors of the coffee supply chain.

The risks have been identified through a comprehensive literature review and validation by industry experts. The paper utilises an interpretive structural modelling (ISM) methodology for developing a hierarchical relationship among the CSFs. Furthermore, fuzzy MICMAC analysis is carried out to categorise these CSFs based on their driving power and dependence value. The fuzzy technique for order preferences by the similarity of an ideal solution (fuzzy-TOPSIS) approach has been applied to prioritise the risks associated with 3PL based on their ability to influence the CSFs of the coffee SC. Furthermore, we performed a sensitivity analysis to analyse the stability of the results obtained in this study.

This study illustrates ten risks associated with 3PL and five CSFs in the coffee supply chain. The analysis revealed that coffee enterprises need to develop a balanced pricing strategy to ensure a sustainable competitive advantage, whereas the lack of direct customer communication is the most dominant 3PL risk affecting the CSFs.

This research provides coffee enterprises with a generalised framework with set parameters that can be used to attain a successful coffee supply chain in any developing nation.

The study contributes to the literature by being the first kind of study, which has used fuzzy ISM-MICMAC to analyse the CSFs of the coffee supply chain and fuzzy-TOPSIS for analysing the impact of various risks associated with the 3PL in the coffee supply chain. Thus, this work can be considered a benchmark for future research and advancement in the coffee business field.

The purpose of this paper is to benchmark alternatives of decision problems that include risk and uncertainty considering different risk attitudes via a new data envelopment analysis (DEA) decision model.

A new utility function of strict bounds is applied in a data envelopment model to evaluate all possible stochastic alternatives (i.e. gambles). The amount of risk in the alternatives is measured by a newly introduced risk ratio (RR). Each alternative is considered as a decision making unit (DMU). The alternatives efficiency frontier is found via linear optimization of the DEA model.

In contrast to literature studies of binary decision alternatives, here, benchmarking is conducted to evaluate multiple decision alternatives with unbounded utility of the payoffs along with a new DEA decision model. Different surveys and studies have been used to validate the model. DEA could demonstrate the ability to uncover relationships that remain hidden for other methodologies. The resulting rankings remarkably conform to those elicited by subjects.

Individuals of different wealth backgrounds evaluate risky decision problems differently.

The paper contributes to the existing research by benchmarking multiple alternatives as compared to the literature research which usually assesses binary problems. Instead of using explicit utilities, the model implements the efficiencies along with a new utility function and a new RR. The introduction of DEA to such a decision field is found to be successful in benchmarking numerous alternatives under different risk attitudes.

The purpose of this paper is to assess and benchmark Six Sigma strategies in services sector, namely, the telecom field, by establishing tables of fallouts of non-conforming services and their associated costs along with a custom data envelopment model for benchmarking the different strategic alternatives.

Under normality assumption, process fallout in Six Sigma is around 0.002/3.4 part per million for a centered/shifted process. By introducing Six Sigma to applications in services sector, normality assumption may no longer be valid; hence, fallouts of non-normal attributes are computed for different one-sided quality levels. The associated costs of strategy deployment, fallout and transaction completion are all considered. Data envelopment analysis model is also established to benchmark the Six Sigma strategic plans. The strategies are detailed down to processes and to quality characteristics which constitute the decision-making units. The efficiency of each service unit is computed using both CCR and super efficiency models.

The amount of efforts/costs needed to reduce the variation in a service may differ according to the targeted quality level. For the same Six Sigma quality level, services demonstrate different performance/efficiencies and hence different returns. In some scenarios, moderate quality levels could present high efficiencies as compared to services of higher levels. It was also found that the required improvement is less in the case of Log-normal as compared to normal distributions at some quality levels. This observation is also noted across the presented distributions of this study (Normal, Log-normal, Exponential, Gamma and Weibull).

The deployment of Six Sigma in services is mostly found in time-related concepts such as timeliness of billing, lifetimes in reliability engineering, queueing theory, healthcare and telecommunication.

The paper contributes to the existing research by presenting an assessment model of Six Sigma strategies in services of non-normal distributions. Strategies of different quality levels present diverse efficiencies; hence, higher quality levels may not be the best alternatives in terms of the returns on investment. The computed fallout rates of the different distributions can serve as palm lines for further deployment of Six Sigma in services. Besides, the combination of optimization and Six Sigma analysis provides additional benchmarking tool of strategic plans in both manufacturing and services sector.

The purpose of this paper is to investigate the competitive position of the company Inditex in the period 1990-2013 as a case study, identified by academics and professionals as a successful company. The analysis has focussed on the comparison of Inditex with its competitive environment.

The methodology used to achieve the objectives was: data envelopment analysis for the analysis of efficiency and for the second the Tobit regression to determine the factors explaining efficiency. The authors have used additional methodologies such as social networks or cluster analysis.

The individual company analysis reveals that the average efficiency level by years for the period 1990-2013, is relatively high 88.8 percent. The determinants of efficiency have been; the resources of the company in terms of assets whose relationship with is U-shaped curvilinear, where the minimum value (trend change) is produced between years 2002 and 2003. The degree of internationalization of the firm, is positively related to efficiency. As the company increases its expansion, experience and skills, increases efficiency. Finally, the effect of liberalization of textile trade in 2005 had no influence on the efficiency levels.

The limitations involving the methodology, in terms of representativeness, possible generalizations and type of secondary information used, can be offset by the ability to provide good vision and establish alternatives for possible studies.

This paper contributes to the fast-fashion retail industry literature by emphasizing the importance of the case study.