PurposeSmall- and medium-sized enterprises (SMEs) mainly rely on their structure and internal networks to achieve their goals and remain competitive. However, their limited internal capabilities and complex environments can hinder their stability. Thus, this study evaluated the relationships among specific factors toward fostering organizational resilience (OR) in tourism SMEs.Design/methodology/approachA multi-methodological approach was adopted to address this research study, including (1) social network analysis (SNA) to formulate the conceptual model and (2) construct validation through partial least squares path modeling (PLS-PM).FindingsThe six proposed hypotheses were supported. These results suggest that addressing these variables and relationships after considering management style and people development as critical factors can foster OR in tourism SMEs.Research limitations/implicationsThe ideas that were developed were constrained to the organizational domain. Although the results apply to the Mexican context, this limitation can be offset by extending the proposal to other emergent regions or organizations. This can also increase the generalization of the results and foster improvements in the approaches applied.Practical implicationsAcademics and managers must rethink resilience as the final state generated by multiple factors. This requires reconfiguring inner organizational interactions, providing more autonomy to operative units, reinforcing business intelligence and improving feedback mechanisms.Originality/valueThis research study contrasts previous studies because it proposes that SNA be exploited to avail of the advantages it confers in designing the conceptual model. In this regard, we present new relationships to promote OR and provide new avenues in order to improve the analysis of adaptation processes.

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The objective of this paper is to estimate the operational efficiency of Mexican water utilities and identify the context variables that impact their efficiency. In particular, a bootstrap data envelopment analysis (DEA) and a bootstrap truncated regression analysis are combined in a two-stage research method. In the first stage, an input-oriented DEA model is used to determine bootstrap efficiency scores. Then, the corrected distribution function of the efficiency scores is used to estimate a truncated regression which is aimed to identify the significant influential context variables. Three categorical and two continuous context variables are considered in the analysis. Results show that only one context variable has a significant impact on the water utilities efficiency scores. Managerial recommendations are drawn from the analysis. It is suggested that water utilities continue or implement wastewater treatment, persist in decreasing and controlling leakage across the distribution network, and maximizing sewer coverage.

This study presents a metaheuristic based on a multiobjective evolutionary algorithm to solve a biobjective mixed-integer nonlinear programming model for supply chain design with location-inventory decisions and supplier selection. The supply chain has four echelons with suppliers, plants, distribution centers, and retailers. The decision variables are the opening of plants and distribution centers and the flow of materials between the different facilities, considering a continuous review inventory policy. The conflicting objectives are to minimize total costs on the entire chain, and to maximize a combined value of overall equipment effectiveness from suppliers. Small-and medium-sized scenarios are solved and compared with Pareto fronts obtained with commercial optimization software applying the epsilon-constraint method. The numerical results show the effectiveness of the proposed metaheuristic. The main contributions of this work are a new practical problem that has not been analyzed before, and the development of the evolutionary algorithm.

This paper introduces the multi-depot open location routing problem (MD-OLRP) with a heterogeneous fixed fleet. The problem is inspired by the collection problem of a company which collects raw materials from different suppliers coordinating several carriers. Each carrier has a heterogeneous fixed fleet. Moreover, there is a fixed cost for contracting each vehicle and a variable cost associated with the distance traveled. The empty haul return to the vehicles depot is not considered in the cost. The raw materials collected are delivered to a single delivery point. The problem is modeled as a Mixed Integer Linear Program (MILP) that minimizes the total cost, selecting the carriers to be contracted, the vehicles to be used from each contracted carrier and the collection routes. For small instances, the model can be solved to optimality. However, approximate procedures are necessary to handle larger instances. In this sense, in the present work we propose an intelligent metaheuristic which incorporates problem specific knowledge to solve it. The computational results show that the solution method is computationally efficient and provides high quality solutions. In particular, the new solution obtained for the case of study generates savings of 30.86% to the company.The main contributions of the paper are the new problem statement that was not found in the literature, its association to the real problem of a company and the intelligent metaheuristic proposed to solve it. Additional experimentation used the model proposed to solve a simpler problem obtaining new best solutions compared to those reported in the recent literature.

In today’s automotive industry, Lean production systems are used successfully to reduce delivery times. The current case study addresses a problem that affects an automotive company, which is the excessive delivery time of a spare part to its both national and international authorized dealers. In order to reduce the delivery time of this replacement part, the Lean Manufacturing methodology was used. For this purpose, the value stream mapping and the proposed A3 report are the tools used. With the use of these tools, activities that did not add any value are eliminated or modified; in addition, the logistical flow of the modules of the door-side trim panel delivery process is improved. As a result, added value is increased, the delivery time is reduced (for Mexico) and the number of product variants is reduced. Now, the painting process is done by the authorized dealers, and the number of pieces used for every spare part was estimated. The study demonstrates that the integration of value stream mapping administrative/productive in conjunction with the A3 report proposal allows to identify and eliminate waste in the delivery process.

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