Integration of IPA and QFD to assess the service quality and to identify after sales service strategies to improve customer satisfaction – a case study

Customer satisfaction is considered very essential nowadays as it shows how firms are dedicated to afford quality products or services to their customers. Retaining the existing customer and acquiring the new customers are the basic objectives of any organisation and after sales service (ASS) has acquired a strategic role as a mean to achieve customer satisfaction. Importance–performance analysis (IPA) and quality function deployment (QFD) are the powerful tools successfully applied in many fields. However, studies on application of these tools in investigating the ASS quality and customer satisfaction seems to be scarce. This article investigates linking of IPA, which is a simple and effective customer satisfaction tool and QFD in the improvement of ASS attributes in an effort to determine the appropriate ASS strategic action plans to be adopted with the objective of enhancing customer satisfaction. In this study, a customer-driven model is proposed to examine the importance of the various ASS attributes and the performance of the organisation via questionnaire survey, and through the IP analysis, the areas to be focused are identified to help the decision makers in devising suitable policies, to improve the ASS performance. This is achieved through the employment of QFD that will help decision makers in the strategic planning to attain better customer satisfaction. A case study is carried out to exhibit the effectiveness of the developed model in a firm involved in manufacturing the home appliances.     

Behavioral aspects of corporate planning

Most models of corporate planning neglect to include behavioral variables. This is unfortunate, as human behavior is typically the most dynamic component of any planning system. Should behavioral variables be overlooked, due to their difficult measurability, or for other reasons, the planning system will inevitably prove deficient in terms of predictability and control. Accounting for human resources and other behavioral measurements should be routinely included in any corporate planning model. A component of such a system would include the output from a stochastic process model of expected future values of employee services. The theoretical development of such a model is briefly discussed in this paper.     

Impact of customer loyalty and service operations on customer behaviour and firm performance: empirical evidence from UK retail sector

Abstract

Retail networks are striving to achieve competitive advantage by increasing value through loyalty and efficiency with a focus on service operations. As sales promotions have become an integral part of the retail supply chain planning, customer behavioural aspects based on loyalty and service operations have been challenged greatly. Subsequently, management capabilities, such as planning and timely replenishment, have become complicated tasks for many retail store managers. This study develops a model integrating retail network value and efficiencies with customer behaviour and performance. We validate the model using survey data from prominent U.K. retail store customers. Our data analysis shows that both loyalty and service operation attributes have positive significant impact on customer behaviour, while the service operation mediates the relationship between loyalty and customer behaviour. This result gives a new outlook to build managerial capability based on customer loyalty and service operations. Our results specifically show that the service operation attributes will indirectly influence the customers’ buying behaviour even in the presence of loyalty attribute such as promotion schemes. This result sends a strong signal to retail supply chain managers to offer customised promotions considering local community rather than having uniform sales promotion nationwide.     

A Service Provider's Elicitation of Its Customers’ Demand Distributions by a Price Mechanism

In a service environment a service provider needs to determine the amount and kinds of capacity to meet customers’ needs over many periods. To make good decisions, she needs to know the probability distribution of her customers’ demand in each period. We study a situation in which customers’ demand for a given service is random in each period, but inelastic, or modeled well by this assumption, and cannot be delayed to the next period. This article presents a mechanism that allows a service provider to learn the distribution of a customer's demand by offering him a set of contracts through which he can partially prepay for future service for a reduced cost for units of service based on anticipated needs. We describe the form of a set of contracts that will cause the customer to reveal his demand distribution as he minimizes his expected costs. To justify the effort of organizing and offering contracts, we present an application that demonstrates the cost savings to the service provider with better capacity planning using the truthfully elicited distribution.     

The Impact of Revenue‐Maximizing Priority Pricing on Customer Delay Costs

Speed is an increasingly important determinant of which suppliers will be given customers' business and is defined as the time between when an order is placed by the customer and when the product is delivered, or as the amount of time customers must wait before they receive their desired service. In either case, the speed a customer experiences can be enhanced by giving priority to that particular customer. Such a prioritization scheme will necessarily reduce the speed experienced by lower‐priority customers, but this can lead to a better outcome when different customers place different values on speed. We model a single resource (e.g., a manufacturer) that processes jobs from customers who have heterogeneous waiting costs. We analyze the price that maximizes priority revenue for the resource owner (i.e., supplier, manufacturer) under different assumptions regarding customer behavior. We discover that a revenue‐maximizing supplier facing self‐interested customers (i.e., those that independently minimize their own expected costs) charges a price that also minimizes the expected total delay costs across all customers and that this outcome does not result when customers coordinate to submit priority orders at a level that seeks to minimize their aggregate costs of priority fees and delays. Thus, the customers are better off collectively (as is the supplier) when the supplier and customers act independently in their own best interests. Finally, as the number of priority classes increases, both the priority revenues and the overall customer delay costs improve, but at a decreasing rate.     

Integrated planning of inbound and outbound logistics with a Rich Vehicle Routing Problem with backhauls

This paper addresses the integration of the planning decisions concerning inbound logistics in an industrial setting (from the suppliers to the mill) and outbound logistics (from the mill to customers). The goal is to find the minimum cost routing plan, which includes the cost-effective outbound and inbound daily routes (OIRs), consisting of a sequence of deliveries of customer orders, pickup of a full truck-load at a supplier, and its delivery to the mill. This study distinguishes between three planning strategies: opportunistic backhauling planning (OBP), integrated inbound and outbound planning (IIOP) and decoupled planning (DIOP), the latter being the commonly used, particularly in the case of the wood-based panel industry under study. From the point of view of process integration, OBP can be considered as an intermediate stage from DIOP to IIOP. The problem is modelled as a Vehicle Routing Problem with Backhauls, enriched with case-specific rules for visiting the backhaul, split deliveries to customers and the use of a heterogeneous fleet. A new fix-and-optimise matheuristic is proposed for this problem, seeking to obtain good quality solutions within a reasonable computational time. The results from its application to the wood-based panel industry in Portugal show that IIOP can help to reduce total costs in about 2.7%, when compared with DIOP, due to better use of the delivery truck and a reduction of the number of dedicated inbound routes. Regarding OBP, fostering the use of OIRs does not necessarily lead to better routing plans than DIOP, as it depends upon a favourable geographical configuration of the set of customers to be visited in a day, specifically, the relative distance between a linehaul that can be visited last in a route, a neighboring backhaul, and a mill. The paper further provides valuable managerial insights on how the routing plan is impacted by the values of business-related model parameters which are set by the planner with some degree of uncertainty. Results suggest that increasing the maximum length of the route will likely have the largest impact in reducing transportation costs. Moreover, increasing the value of a reward paid for visiting a backhaul can foster the percentage of OIR in the optimal routing plan.     

The planning of a department store

A town or village attracts people from its hinterland to purchase goods by virtue of the amount and variety of goods on offer. Similarly, a department store attracts customers away from cempetitors by means of displays, staff expertise, stock holdings and numerous other parameters. The store is generally free to manipulate these parameters subject to certain restrictions; the manipulation will have a direct affect on the ultimate profitability of the store. This paper describes some current research that is being carried out in conjunction with a department store group. The ultimate aim is to link the corporate planning of the group and each store to detailed socioeconomic data describing the population. Some aspects of the problem have been investigated in depth, some are currently being discussed and some have not been considered at all as yet. The latest position will be reported and hopefully some feedback will be engendered.     

Integration between flow scheduling and personnel allocation in a parallel line system in automotive industry

A state-of-the-art review over fifty years of flow shop scheduling research, written by Gupta and Stafford (2006), comes to the conclusion that the mathematical theory of flow shop scheduling “suffers from too much abstraction and too little application”. In this paper we will develop an extended mathematical model for flow shop scheduling with parallel lines and simultaneously a worker assignment to machines as well as a solution concept for practical use. Such production systems are realized by applying the BTO-(Build to order) concept, as can be found in the automotive or computer industry, which allows customers to make any changes to their vehicles or hardware configuration within a few days before final assembly. In these cases late configuration is an important task for the producer and a complex scheduling problem arises in this context.     

Codes of ethics and firm size: A stakeholder approach to strategic planning

A firm's capital budgeting and strategic planning decisions have the potential to affect many groups of people called stakeholders. A stakeholder is any group or individual who can affect or is affected by the achievement of the firm's objectives. This study examines whether the presence of a code of ethics that specifically addresses capital budgeting/strategic planning decisions will significantly raise the awareness of social responsibility during the long-run planning process. This study also examines whether firm size is associated with the awareness of social responsibility during the long-run planning process. Support was found that a code of ethics that addresses long-range planning is associated with higher awareness during the planning process. Firm size was not found to be statistically different.     

Static-dynamic uncertainty strategy for a single-item stochastic inventory control problem

We consider a single-stage inventory system facing non-stationary stochastic demand of the customers in a finite planning horizon. Motivated by the practice, the replenishment times need to be determined and frozen once and for all at the beginning of the horizon while decisions on the exact replenishment quantities can be deferred until the replenishment time. This operating scheme is refereed to as a “static-dynamic uncertainty” strategy in the literature [3]. We consider dynamic fixed-ordering and linear end-of-period holding costs, as well as dynamic penalty costs, or service levels. We prove that the optimal ordering policy is a base stock policy for both penalty cost and service level constrained models. Since an exponential exhaustive search based on dynamic programming yields the optimal ordering periods and the associated base stock levels, it is not possible to compute the optimal policy parameters for longer planning horizons. Thus, we develop two heuristics. Numerical experiments show that both heuristics perform well in terms of solution quality and scale-up efficiently; hence, any practically relevant large instance can be solved in reasonable time. Finally, we discuss how our results and heuristics can be extended to handle capacity limitations and minimum order quantity considerations.     

Planning innovation

This paper deals with the concept of planning for innovation, using marketing as a basis for that planning. The author claims that marketing really controls the whole operation of planning for innovation, even the details of development and design, because customers not only use the resulting product or service; they pay for it and make everything possible.     

Inventory Commitment and Prioritized Backlogging Clearance with Alternative Delivery Lead Times

We propose a model where customers are classified into two groups: short lead‐time customers who require the product immediately and long lead‐time customers to whom the supplier may deliver either immediately or in the next cycle. Unmet orders are backlogged with associated costs. Specifically, the supplier faces two problems: how the on‐hand inventories should be allocated between the two classes of customers and how the backlogged orders should be cleared when replenishments arrive. We treat the former as an inventory commitment problem and handle the latter with priority rules. We characterize and compare the inventory commitment policies with three priority rules in clearing backlogs. We also explore the optimal inventory replenishment decision and evaluate the performance of each priority rule.     

Environmental forecasting and non-profit professional organizations

To undertake any kind of realistic planning activity, it is useful to have a long-term environmental forecast which provides the planner with an overall perspective. The planner will be functioning over the next decade in a very dynamic, complex and challenging political, economic, technological and social environment, and will require very effective planning efforts to cope with such changing environment. This article presents an approach and methodology that a planner could use in his/her organization's planning process. To the best of our knowledge, very few organizations—profit and non-profit oriented—undertake a formal long-term environmental forecast. This article might encourage several planners to examine this area of long range planning in their respective organizations. The long- term environmental forecasting approach presented in this article could be applied by planners in all types of organizations—small or large, profit oriented or non-profit oriented, old or new. This article, however, is based on a study which the authors did for a non-profit organization.     

Loyalty-based segmentation and the customer development process

As process management fast becomes recognised as the means by which customer value can be created, it is now equally well understood that the mechanism of value delivery is among the core processes. Without managing Customer Development as a core process, the implementation of strategic plans will lack clear focus. The author argues that the function of the Customer Development process is to build relationships with preferred customers. Working on the premise that all customers are not created equal, the priority for customer development in mature markets is to build these preferred relationships among existing customers. It is now accepted wisdom that these customer relationships deliver superior profits. How customer development management select these customers, or groups of customers, and build specific relationships is directed by the Principles of Loyalty Management.These principles acknowledge that customer loyalty is relative which means that customers as well as product and service brands need to be differentiated. The Diamond of Loyalty© provides a new management tool for this purpose by categorising customer purchasing styles according to their level of involvement (i.e. brand or company relationship) and their purchasing portfolio across suppliers.Finally, it is argued that customer development should discriminate in favour of supporting `high share' customers over `low share' customers in building preferred relationship among existing customers.     

Flexible‐Duration Extended Warranties with Dynamic Reliability Learning

Frequent technological innovations and price declines adversely affect sales of extended warranties (EWs) as product replacement upon failure becomes an increasingly attractive alternative. To increase sales and profitability, we propose offering flexible‐duration EWs. These warranties can appeal to customers who are uncertain about how long they will keep the product as well as to customers who are uncertain about the product's reliability. Flexibility may be added to existing services in the form of monthly billing with month‐by‐month commitments or by making existing warranties easier to cancel with pro‐rated refunds. This paper studies flexible warranties from perspectives of both customers and the provider under customers' reliability learning. We present a model of customers' optimal coverage decisions and show that customers' optimal coverage policy has a threshold structure under some mild conditions. We further show that flexible warranties can result in higher profits and higher attach rates in a homogeneous market as well as in a heterogeneous market with multiple segments differing in various dimensions.     

An Empirical Test of the Strategic-Grid Model of Information Systems Planning*

Contingency models of information systems planning predict that no single planning approach will suit all organizations' needs. Little empirical research has been undertaken, however, to evaluate this prediction. Accordingly, we used McFarlan, McKenney, and Pyburn's (1983) strategic-grid model to study the information systems planning problems encountered by 49 governmental agencies. Twenty-seven agencies were required to follow a planning approach best suited to organizations that had a high level of dependence on both their existing and proposed systems. We predicted that agencies not having these characteristics would encounter the most problems with the approach. The remaining 22 agencies could choose their own planning approach. We studied this latter group to determine whether the problems encountered by the first group could be attributed to the mandated approach. Overall, the empirical results obtained were equivocal. Some results indicated that more planning problems were encountered by agencies in which the mandated approach was not appropriate to their position in the strategic grid. Other results were not supportive of this proposition. More work needs to be undertaken, therefore, to evaluate the predictive and explanatory power of contingency models of information systems planning. In addition, our research indicates a need to develop more rigorous theories of information systems planning behaviors, to improve the instruments needed to measure these behaviors, to explore the relationship between information systems planning behaviours and organizational effectiveness, to investigate how organizational learning impacts planning behaviors, and to determine the types of information systems planning problems that diffuse through organizations and those that remain localized.     

Joint product assortment,inventory and price optimization to attract loyal and non-loyal customers

In this paper, we analyze the emerging retail practice of carrying a combined product assortment consisting of both regular “standard” products and more fashionable and short-lived “special” products. The purpose of this practice is to increase store traffic by attracting heterogeneous classes of customers, which drives up sales of standard products due to the potential cross-selling effect. Customers who are primarily attracted by special products will also buy some standard products. In this context, we analyze three decisions that are crucial for a retailer׳s commercial success: the product assortment, the inventory levels and the pricing. We propose an optimization model and an iterative heuristic to analyze the trade-offs between the combined product assortment, the inventory level and the price per product when there is limited shelf space. Using numerical experiments, we show that our heuristic can be trusted and that its accuracy improves when the number of products increases. Our findings indicate that to attract more customers for standard products, a retailer may benefit from carrying low priced special products which, if considered in isolation, would be non-profitable. As the cross-selling effect decreases, a retailer should focus more on the standard assortment by increasing its size and decreasing the prices. However, introducing special products and ignoring the cross-selling effect may decrease a retailer׳s profitability. We show that the introduction of special products involves more than just choosing the right specials for non-loyal customers but impacts the global assortment planning, the standard products and the products pricing.     

数据可携权能否治理“大数据杀熟”？

电商平台利用大数据对消费者“杀熟”的现象屡见不鲜,但因其隐蔽性我国政府一直难以监管,那么欧盟提出的消费者数据可携权能否治理“大数据杀熟”现象？对此本文从平台用户的视角出发,通过构建由电商平台和消费者组成的演化博弈模型,研究引入数据可携权后双方的演化稳定策略,并分析影响双方行为策略的因素。研究表明：当老顾客在平台用户中占比较高,并且老顾客行使数据可携权转移至新平台获得的额外效用大于某阈值时,赋予消费者数据可携权能够遏制 “大数据杀熟”现象,但当老顾客中不满意顾客的占比较高时,消费者具有数据可携权会阻碍电商平台产品或服务的提升;消费者行使数据可携权的概率与个人数据价值成正相关,与观测数据价值成负相关;电商平台采取“大数据杀熟”策略的概率与个人数据价值成正相关,与衍生数据价值成负相关。     

Advertising in Asymmetric Competing Supply Chains

Advertising is a crucial tool for demand creation and market expansion. When a manufacturer uses a retailer as a channel for reaching end customers, the advertising strategy takes on an additional dimension: which party will perform the advertising to end customers. Cost sharing (“co‐operative advertising”) arrangements proliferate the option by decoupling the execution of the advertising from its funding. We examine the efficacy of cost sharing in a model of two competing manufacturer–retailer supply chains who sell partially substitutable products that may differ in market size. Some counterintuitive findings suggest that the firms performing the advertising would rather bear the costs entirely if this protects their unit profit margin. We also evaluate the implications of advertising strategy for overall supply chain efficiency and consumer welfare.     

Self‐Selecting Priority Queues with Burr Distributed Waiting Costs

Service providers, in the presence of congestion and heterogeneity of customer waiting costs, often introduce a fee‐based premier option using which the customers self‐segment themselves. Examples of this practice are found in health care, amusement parks, government (consular services), and transportation. Using a single‐server queuing system with customer waiting costs modeled as a Burr Distribution, we perform a detailed analysis to (i) determine the conditions (fees, cost structure, etc.) under which this strategy is profitable for the service provider, (ii) quantify the benefits accrued by the premier customers; and (iii) evaluate the resulting impact on the other customers. We show that such self‐selecting priority systems can be pareto‐improving in the sense that they are beneficial to everyone. These benefits are larger when the variance in the customer waiting costs is high and the system utilization is high. We use income data from the poorest and richest areas (identified by zipcode) in the United States along with the countrywide income distribution to illustrate our results. Numerical results indicate that planning for a 20–40% enrollment in the high‐priority option is robust in ensuring that all the stakeholders benefit from the proposed strategy.