Customer interaction in new service development has a positive impact on the performance of new services. In addition, prior studies recognize the importance of the fuzzy front-end stages of new service development. Yet, the researchers have not taken the next step to explore the relationship between these two key areas of service innovation. To address this critique of the literature, the process of customer interaction in the fuzzy front-end of new service development is investigated by conducting a rigorous qualitative field research involving 26 financial services firms. The findings suggest that the fuzzy front-end can be much less ‘fuzzy’ if customers are involved in the front-end stages of new service development.
Purpose The purpose of this paper is to explore conceptualizations of mindset across disciplines with particular attention to scholars’ care in defining and operationalizing the construct of mindset. Theories of mindset have witnessed increased attention through a variety of disciplines for their applicability as processes with the potential to influence individual and/or organizational outcomes. Exploration of mindset conceptualizations and characterizations reveal substantial divergences. Design/methodology/approach This conceptual paper generally examines the utilization of mindset constructs via a multidisciplinary review of literature and specifically details three mindset theories (implemental and deliberative, global and growth and fixed mindsets) to illuminate such disparities. Findings This paper categorizes the significant variations of the mindset construct and research via three distinct streams. Each stream highlights knowledge as instrumental in the mindset construct; however, the ways in which varying aspects of knowledge, knowledge mechanisms or knowledge as a component of an individuals and/or organization’s identity correspond to the inherent presuppositions of varying articulations of mindset theory and praxis. Practical implications Effectively influencing an individual and/or organization’s mindset necessitates an accurate assessment of the mindset construct. Further, evaluating the applicability of mindset research and/or feedback from a consultant warrants attention to the assumptions undergirding the mindset construct. Originality/value Generally, mindset studies and theories have scantly attended to both the historical development of mindset research as well as divergences in the research record within and across disciplines. This paper attempts to address this deficiency. Further, this paper appears to be the first attempt to compare and identify varying conceptualizations and characterizations of mindset theory and, therefore, identifies previously unidentified assumptions.
This paper proposes a parametric programming approach to address the notion of the time value of delays in the presence of mixed (random and fuzzy) uncertainties that result from unreliable systems. To consider different types of delay time values, the system states are appropriately and carefully identified and defined, and a cost-based fuzzy decision model that incorporates several unreliability factors is constructed. Then, the proposed model is transformed into a pair of nonlinear programs parameterized by the possibility level to identify the lower and upper bounds on the minimal total cost per unit time at and thus construct the membership function. To provide analytical expressions, a special case with analytical results is also presented. In contrast to existing studies, the results derived from the proposed solution procedure conserve the fuzziness of the input information, representing a significant difference from the crisp results obtained using approaches based on probability theory. The results indicate that the proposed approach can provide more precise information to managers and improve decision-making in practical system design.
Why is it so plausible that business organisations in contemporary society use values in their communication? In order to answer this question, a sociological, system theoretical approach is applied which approaches values not pre-empirically as invisible drivers for action but as observable semantics that form organisational behaviour. In terms of empirical material, it will be shown that business organisations resort to a communication of values whenever uncertainty or complexity is very high. Inevitably, value semantics are applied in organisations first when the speakers are uncertain about which stakeholders to whom they have to address (uncertainty) or when different stakeholder groups have to be addressed simultaneously (complexity); second, when the identity of the organisation has to be described; and third, when future strategic options that cannot be expressed by quantitative terms have to be communicated. Values accordingly play a role in organisational practice when certain aspects are indeterminate. Therefore, they are a means for organisations to communicate under fuzzy circumstances. On the basis of these findings, new approaches to value management can now be formulated.
Project scheduling problem is to determine the schedule of allocating resources so as to balance the total cost and the completion time. This paper considers project scheduling problem with mixed uncertainty of randomness and fuzziness, where activity duration times are assumed to be random fuzzy variables. Three types of random fuzzy models as expected cost minimization model, ( , )-cost minimization model and chance maximization model are built to meet different management requirements. Random fuzzy simulations for some uncertain functions are given and embedded into genetic algorithm to design a hybrid intelligent algorithm. Finally, some numerical experiments are given for the sake of illustration of the effectiveness of the algorithm.
Economic production quantity (EPQ) is the quantity of a product that should be manufactured in a single batch so as to minimize the total cost. In classical model EPQ only applies where the demand for a product and production rate is constant over the year. But in reality these parameters vary with time in different scenarios. In this paper we have considered a production inventory model for deteriorating items with ramp type demand rate under the effect of inflation and shortages under fuzziness. The deterioration rate is represented by a two-parameter Weibull distribution. As inflation erodes the value of money so we have also considered the effect of inflation when there is shortage in the stock under finite time horizon. Some parameters are vaguely or unclearly defined or whose values are imprecise or determined based on subjective beliefs of individuals. Therefore the inventory model is solved under fuzzy environment to evaluate the optimum solution of the model in different cases. We have optimized our solution by considering production time and production rate as decision variables in two separate cases. While incorporating symmetric triangular fuzzy number we use total λ-integral value to defuzzify the solution. Finally, utility of the model is presented by using some numerical examples and sensitivity analysis and the results are analyzed.
In logistics system, facility location–allocation problem, which can be used to determine the mode, the structure and the form of the whole logistics system, is a very important decision problem in the logistics network. It involves locating plants and distribution centers, and determining the best strategy for allocation the product from the plants to the distribution centers and from the distribution centers to the customers. Often uncertainty may be associated with demand, supply or various relevant costs. In many cases, randomness and fuzziness simultaneously appear in a system, in order to describe this phenomenon; we introduce the concept of hybrid variable and propose a mixed-integer programming model for random fuzzy facility location–allocation problem. By expected value and chance constraint programming technique, this model is reduced to a deterministic model. Furthermore, a priority-based genetic algorithm is designed for solving the proposed programming model and the efficacy and the efficiency of this method and algorithm are demonstrated by a numerical example. Till now, few has formulated or attacked the FLA problems in the above manner. Furthermore, the techniques illustrated in this paper can easily be applied to other SCN problems. Therefore, these techniques are the appropriate tools to tackle other supply chain network problems in realistic environments.
Purpose - The purpose of this paper is to discuss the applicability of investment decision-making techniques under fuzziness.Design methodology approach - The paper explains how fuzzy sets can be used in investment decision making.Findings - It was found that any classical investment analysis technique can be converted easily to a fuzzy case.Originality value - The paper indicates the necessity for usage of the fuzzy set theory in case of incomplete information.
This paper considers several models of product-mix decision problems and production planning problems under uncertain conditions, and shows that these are extensional and versatile models for resolving previous product-mix problems. These proposed models include randomness derived from statistical analysis based on historical data, ambiguity of decision maker's intuition and the quality of received information, and flexibility in accomplishing the original plan. Furthermore, given that the upper limit values of some constraints have flexibility, and given a decision maker's level of satisfaction, we propose a flexible product mix of problems using the theory of constraints (TOC), and develop an efficient solution method. We then provide a numerical example that compares our models with some previous basic models. Efficiency of flexibility is obtained when our proposed models are applied to several conditions, such as measurable changes from the expected value of future returns.