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The objective of this paper is to present the employment of the new hierarchical fuzzy technique for order preference by similarity to ideal solution (TOPSIS) approach to evaluate the most suitable business process outsourcing (BPO) decision.

The paper explains the importance of selection criteria for evaluation of BPO. It then describes briefly the fuzzy hierarchical TOPSIS methodology. There then follows a discussion of the application of the fuzzy hierarchical TOPSIS with some sensitivity analysis to the BPO evaluation problem. Finally, some concluding remarks and perspectives are offered.

Use of the hierarchical fuzzy TOPSIS methodology offers a number of benefits. It is a more systematic method than the other fuzzy multi‐criteria decision‐making (FMCDM) methods and it is more capable of capturing a human's appraisal of ambiguity when complex multi‐criteria decision‐making problems are considered. The hierarchical fuzzy TOPSIS is superior to the other FMCDM methods, such as fuzzy analytic hierarchy process (FAHP) and classical fuzzy TOPSIS methods, since the hierarchical structure without making pairwise comparisons among criteria, sub‐criteria, and alternatives is considered. Hierarchical fuzzy TOPSIS is an excellent tool to handle qualitative assessments about BPO evaluation problems, and its calculations are faster than FAHP. Also, hierarchical fuzzy TOPSIS makes it possible to take into account the hierarchical structure in the evaluation model. However, there are drawbacks. The classical fuzzy TOPSIS is a highly complex methodology and requires more numerical calculations in assessing the ranking order of the alternatives than the hierarchical fuzzy TOPSIS methodology and hence it increases the effort, thus limiting its applicability to real world problems.

The proposed model will be very useful to managers in the manufacturing sector, as this method makes decision making easier, systematic, efficient and effective.

The paper attempts to construct a novel multi-objective grey hierarchical group consensus approach to deal with the group consensus problems consisting of hierarchical relationship and non-cooperative behaviors among decision makers (DMs).

To deal with these group consensus problems consisting of hierarchical relationship and non-cooperative behaviors among DMs non-cooperative behavior in uncertain information systems, considering the influence of coordination cost and the degree of group consensus, based on the idea of grey situation decision-making, the authors establish a multi-objective grey hierarchical group consensus model, and design different invalid decision elimination rules for decision-making groups of different sizes, and use a case verifies the effectiveness and feasibility of the model.

With the continuous improvement of the coordination cost budget, the degree of consensus of all departments and the overall consensus tend to be stable, and will no longer change with the increase of the coordination cost budget. The cost required by each department is basically consistent with the response trend of the cost required to coordinate the overall situation to the pre-set lower limit of group consensus.

The proposed approach can succeed in identifying DMs' information, and mine the DMs' information and help make a relatively more scientific decision.

Previous literature has compared the effectiveness of different styles of leadership, yet most of this research has not compared different levels of analyses regarding leader styles or behaviors. This shortcoming often limits our understanding of how leadership acts on a phenomenon of interest to a single level of analysis. This article develops a computational model and describes a levels-based comparison of four types of leadership that represent three different levels: individual, dyad, and group. When examined across a dynamic group decision-making optimization scenario, group-based leadership is found to produce decisions that are closer to optimal than dyadic-based and individual-based leadership. An alternative computational model varying individual cognitive and experience-based components among group members also indicates that group-based leadership produces more optimal decisions. First published in Leadership Quarterly (Dionne, S. D., & Dionne, P. J. (2008). Levels-based leadership and hierarchical group decision optimization: A simulation. Leadership Quarterly, 19, 212–234), this version offers an updated introduction discussing simulation as a theoretical development tool and supplies additional evidence regarding the growth of simulation methods in leadership research.

In the process of group decision-making, there may be multilayer subjects. In other words, members of the decision-making group may come from different layers and there is interest game among decision experts. Therefore, it is an extremely important topic to aggregate the information of decision experts who are involved in hierarchical relations and gaming relations so as to effectively address game conflicts and reach game cooperation.

First, a programming model is established to minimize the difference of expert opinions in hierarchical decision-making, and the method to solve the optimal solution is given. Second, the cooperative game model and its properties are discussed by using cooperative game and Shapley value, and the method to determine the weight vector between layers is also proposed.

This model can quickly aggregate information and achieve game equilibrium among decision-makers with hierarchical relationships. It can be widely used in decision evaluation with hierarchy structure and has certain practical value.

In order to solve the problem that experts at different levels may have conflicts of interest in multilayer grey situation group decision-making process, cooperative game and Shapley value theory are introduced into the study, and a multilayer grey situation group decision-making model based on cooperative game is constructed. The validity and practicability of the model are illustrated by an example.

Supplier selection problem is the key process in decision making of supply chain management. An effective selection of vendors is heavily responsible for the success of any organization. Vendor selection problem (VSP) reflects a more practical view when the decision makers involved in the problem are present on different levels. Moreover, vendor selection consists of various random parameters to be dealt with in real life. The purpose of this paper is to present a decentralized bi-level VSP where demand and supply are normal random variables and objectives are fuzzy in nature. Decision makers are present at two levels and are called as leader and follower. As the next purpose, this paper extends and presents a solution approach for fuzzy bi-level multi-objective decision-making model with stochastic constraints. Different scenarios have been developed within a real-life case study based on different sets of controlling factors under the control of leader.

This study uses chance-constrained programming and fuzzy set theory to generate the results. Stochastic constraints are converted into deterministic constraints using chance-constrained programming. Decision variables in the bi-level VSP are partitioned between the two levels and considered as controlling factors. Membership functions based on fuzzy set theory are created for the goals and controlling factors and are used to obtain the overall satisfactory solutions. The model is tested on a real-life case study of a textile industry and different scenarios are constructed based on the choice of leader’s controlling factors.

Results showed that the approach is quite helpful as it generates efficient results producing a good level of satisfaction for the decision makers of both the levels. Results showed that on choosing the vendors that are associated with worst values in terms of associated costs, vendor ratings and quota flexibilities as controlling factors by the leaders, the level of satisfaction achieved is highest. The level of satisfaction of solution is lowest for the scenario when the leader chooses to control the decision variables associated with vendors that are profiled with minimum vendor ratings. Results also showed that higher availability of materials and budget with vendors proved helpful in obtaining quota allocations. Different scenarios generate different results along with different values of satisfaction degrees and objective values which shows the flexible feature of the approach based on leader’s choice of controlling factors. Numerical results showed that the leader’s control can be effectively incorporated maintaining satisfaction levels of the followers under various scenarios or conditions.

The paper makes a certain contribution toward the study of vendor selection existing in a hierarchical manner under uncertain environment. A wide set of data of different factors is needed which can be seen as a limitation when the available time is short for the supplier selection process.

VSP which is generally adopted by most of the large organizations is characterized with hierarchical decision making. Moreover, dealing with the real-life concern, the data available for some of the parameters are not complete, representing an uncertainty of parameters. This study is quite helpful for decentralized VSP under uncertain environment to reduce the costs, improve profit margins and to create long-term relationships with selected vendors. The proposed model also provides an avenue to explore the decision making when the leader has control over some of the decision variables.

Reviewing the literature available, this is the first attempt to present a multi-objective VSP where the decision makers are at hierarchical levels considering uncertain parameters such as demand and supply as per the best knowledge of authors. This research further provides an approach to construct scenarios or different cases based on the choice of leader’s choice of controlling factors.

Significant transitions in firms (e.g. outsourcing) may impact the relative importance of production and inventory assets, affecting the hierarchical separation of planning decisions. The purpose of this paper is to contribute to planning literature by investigating how the production system and the planning environment influence the performance difference between hierarchical and monolithic planning. Further, it seeks to reduce the prevailing theory-practice gap in tactical planning.

Through an action research study, a monolithic model integrating tactical production planning decisions, subject to upstream supply chain constraints, with strategic investments decisions was developed, tested and implemented in a global OEM. Using the developed model and a measure of the capital cost of production assets relative to the cost of holding inventory, it is numerically examined how the production system and planning environment influence the performance of hierarchical and monolithic planning.

The research demonstrates the potential of integrating decisions and reveals significant performance differences between hierarchical and monolithic planning for firms with low capital cost relative to inventory holding cost.

The findings suggest a fit between planning processes, the production system and planning environment. Future research should empirically validate the findings and propositions.

The paper combine capital investments and production planning decisions, which usually transpire at different hierarchical levels and on different time-horizons, and investigates the consequences of hierarchical separation through a real-life validated case and numerical analysis.

This paper first aims to examine how business process change decisions (BPCDs) were implemented in a government organisation bound by tightly coupled temporal constraints (TTCs). Second, it focuses on how to achieve optimal and efficient BPCDs that require tight compliance with regulators’ temporal constraints. Finally, it formulates a rigorous framework that can facilitate the execution of optimal BPCDs with maximum efficiency and minimal effort, time and cost.

Decision-making biases by individuals or groups in organisations can impede optimal BPC implementation; to demonstrate this, a case study is investigated and the formulated framework is applied to tackle these failings.

The case study analysis shows 76 per cent of the BPCDs implemented were inefficient, mostly because of poor decisions, and these resulted in negative ripple effects. In response, the newly developed hierarchical change management structure (HCMS) framework was used to empower organisations to execute high-velocity BPCDs, enabling them to handle any temporal constraints imposed by regulators or other exogenous factors. The HCMS framework was found to be highly effective, scoring an average improvement of more than 100 per cent when measured using decision quality dimensions. This paper would be of value for business executives and strategic decision makers engaging with BPC.

The HCMS framework has been applied in a single case study as a proof of concept. Future research could extend its application to broader domains that have multi-attribute structures and environments. The evaluation processes of the proposed framework are based on subjective metrics. Causal links from the framework to business process metrics will provide a more complete performance picture.

The outcome of this research assists in formulating a systematic BPCD framework that is otherwise unavailable. The practical use of the proposed framework would potentially impact on quality outcomes for organisations. The model is derived from decision trees and analytical hierarchical processes and is tailored to address this problematic area. The proposed HCMS framework would help organisations to execute efficient BPCDs with minimal time, effort and cost. The HCMS framework contributes to the academic literature on BPCD that leverages diverse stakeholders to engage in BPC initiatives.

The research presents a novel framework –HCMS – that provides a platform for organisations to easily determine and solve hierarchical decision structure problems, thereby allowing them to efficiently automate and institutionalise optimal BPCDs.

The issues of development of decisions are very important during formation of the system of management of modern business systems in the conditions of turbulence of external conditions. The ideas of rational structuring of information flows, which are used for decision making, are related to the necessity for development of communicative culture of companies. Quality of interaction between persons that participate in decision making should be assessed by analyzing the ratio of probabilities that characterize quality of information and correctness of decisions and development of a special model.

The purpose of this paper is to examine international decision making, information processing, and related performance implications. The authors aim to explore the relationship between international decision making and problem-solving dissensions related to entry mode decisions. In addition, they aim to investigate the effects of dissension on entry mode performance, and the moderating effect of the foreign direct investment (FDI) vs non-FDI decision as it relates to dissension-mode performance. Despite their significance from an information processing perspective, these issues have not been sufficiently explored in international entry mode research.

This research presents data collected from 233 privately owned internationalized Chinese firms. The analysis in this investigation includes hierarchical ordinary least squares regression.

The findings suggest an inverse U-shaped relationship between dissension and entry mode performance, as opposed to a linear one, and a moderating effect of FDI vs non-FDI decisions on this curvilinear dissension-performance association. These findings support and refine the rationale of the information processing perspective.

These findings add realistic elements to the alleged “rational” international decision-making doctrine assumed in previous entry mode literature. The findings show the importance of the heterogeneity of information processing in entry mode strategic decision-making processes (SDMPs), and its effects on specific decision types. The authors believe that this is the first empirical study to use an information processing perspective to examine the effects of SDMPs on entry mode performance.

Decision making in networks is multilateral and interaction‐based and is often contrasted with unilateral decision making in a hierarchy. The purpose of this paper is to examine whether unilateral interventions can nevertheless be functional in networks.

A large number of empirical studies into decision making in networks were consulted to examine whether they featured unilateral interventions and, if so, what the roles of these interventions were. Prior to this, the author outlines theories on decision making in networks and the dysfunctions of unilateral interventions.

Six strategies were found in which unilateral interventions proved effective in network‐like decision making. Unilateral action may be used to influence other actors' perceptions of the win‐win game, to change the pattern of interdependencies, as a follow‐up to failed interaction, if room is offered simultaneously, if there is a critical mass of winners and to de‐hierarchize decision making. These unilateral strategies were found to be embedded in interaction‐based, network‐like decision making. In some cases, they stimulated a process of interaction; in other cases, they resulted from a process of interaction.

The strategies show that decision making in networks benefits from the intelligent use of unilateral action.

The paper goes beyond the dichotomy between network and hierarchy and demonstrates that, on the interface of networks and hierarchies, there are many possibilities of developing strategies that – although unilateral – are network‐contingent.