How Kansei Engineering, Kano and QFD improve logistics services
Markus Hartono
1, a, Amelia Santoso
1, Dina Natalia Prayogo
11
Department of Industrial Engineering, University of Surabaya, Indonesia a
Keywords: Kansei Engineering, Kano, QFD, logistics, services
Abstract. In the period of 2004 – 2014, there was a significant growth of employment in logistics sector in Indonesia. It shows that there is an opportunity to probe problems and achieve improvements in logistics sectors. Inherently, it shows a global trend, which is a rapid need for outsourcing the supporting logistics activities. It makes the logistics service provider (known as third-party logistics) has a beneficial portion in the international and domestic supply chain. With regard to the very tight competition, the logistics services should be able to deliver both cognitive and affective customer satisfaction. In the operational point of view, customer satisfaction and lifetime values offered are the critical attributes to the success of logistic services. Mostly, studies in logistic services have been focusing on the service gaps, which is more on cognitive process. Actually, many researches have been conducted in evaluating the logistics service quality using SERVQUAL and Kano model. However, it is relatively insufficient. Hence, a deep understanding of customer affective need (known as Kansei, in Japanese) is highly required, as a competitive advantage to explore and model more comprehensive customer experiences due to perceived certain logistics services. This paper proposes a model of Kansei Engineering, Kano and QFD, which is hoped to generate more innovative ideas for improvements. Surely, those which are critical and sensitive to the customer emotional satisfaction will be of interest. Moreover, it leads to the customer delight, which is beyond satisfaction. A case study in the supporting logistics services has been chosen to validate the proposed model. A survey through face-to-face questionnaire involved 157 customers has been done. Afterwards, the model has been validated, and through House of Quality (HoQ), it has been proposed some innovative improvement ideas. They include the use of apps for order confirmation and cancellation, the integration of Google Maps to the ordering system, pre-order booking, and the feature of bilingual in the transaction menu. Thus, in practical implication and point of view, this study is hoped to provide guideline to the manager of logistics services’ company in capturing, measuring and analyzing the customer emotional need (Kansei), with respect to the service attributes which are highly significant to those Kansei.
Introduction
Perceived service quality will affect satisfaction that leads to customer loyalty. In other words, customer loyalty will be affected by perceived quality indirectly. The service quality can be considered as a composite of multiple service attributes which are structured into tangible and intangible/subjective attributes [1]. The assessment of service quality can be judged by the gap between perceived quality and the customer expectation, which is known as SERVQUAL [2]. The application of SERVQUAL has been extensively broad, since 1990s. In particular service domain, the common dimensions of SERVQUAL discussed are tangibles, reliability, responsiveness, assurance and empathy.
One of the emerging services is that logistics services, especially third-party logistics (3PL). According to Chen et al. [3], this type of logistics services can add a great value to customers and companies. There are three major services offered, such as package pick-up, tracking, and delivery services. Moreover, these services may play a critical part in leveraging the effectiveness and efficiency of the physical distribution and online transactions of goods, even of services [4].
between customers and employees will build service satisfaction. In other words, it is said that processes, activities and interactions are more dominant than things [6; 7]. Regarding human-based interaction, service experiences will produce both cognitive and affective satisfaction (see [8] and [9]).
In obtaining a competitive advantage with respect to customer behavior, services should put more efforts on integrating human factors into service design [10]. The scopes of human factors (known as Ergonomics) cover physical and psychological human behaviors, environments, products and services [3]. Inherently, the concept of Ergonomics has been extensively extended from physical product to service designs. Hence, the service provider should understand how customers expect and perceive the services [11].
Products and services are deemed to be successful when they can produce happiness to the customers or users [12]. Moreover, emotional satisfaction is hoped to be put beyond the usability and functionality [13; 9]. In dealing, capturing and modeling customer emotional needs into service design and development, Kansei Engineering [KE] is proposed [14; 15; 16]. Since 1970s, it is the ultimate ergonomic-based product design development which puts emotions into its core concept, and later quantifies them into design specifications [14].
According to Chen et al. [3], KE has been applied to the design of physical products such as architectural interiors and exteriors, consumer goods, mobile phones, and even sport shoes. Mostly, the designers use Kansei words as the representative of emotional needs which have been translated into product elements. The use of KE in services is deemed to be limited. Its application into services may cover delivery and installation of a washing machine [17], internet services [18], hotel services [16], restaurant services [19], and logistics services [3]. One of the superiorities of KE is that its ability to show the interactive relationship between design characteristics and emotional responses, hereinafter it establishes a quantitative framework.
Regarding the logistics service as one of the emerging services nowadays, KE has been applied, as it has been conducted by Chen et al. [3]. Recent research of KE in logistics services has been done by exploring the quantitative relationship between feelings (using Kansei words) and design elements of home delivery services. It shows that what the most important design elements connected to the critical feelings, which refer to the improvement ideas. However, due to efficiency concern, this study by Chen et al. [3] can be strengthen and extended by incorporating potential quality tools, such as Kano model and QFD. According to Hartono [20], the use of Kano model and QFD in Kansei methodology research may provide a formal methodology which accounts for customer emotional needs in service design. Hence, this study of KE integrated with Kano model and QFD in logistics services is proposed. Kano will help a screening process to identify which service attributes are categorized as one-dimensional (O) and attractive (A) which are critical to Kansei, whereas QFD will finalize the weighted prioritized service attributes to improve [see 16].
Thus, the objective of this study is to develop a conceptual framework of KE, Kano and QFD applied to logistics services, and to conduct an empirical study on IT-based logistics services to test the applicability of the proposed model. The details of the superiority of current integrative framework compared to the individual method are summarized in the table below:
Table 1. The rational contrast between individual method and the proposed integrative framework
Individual method Proposed integrative framework
Kansei Engineering is used as a function between Kansei and service experience, or in other words, it is a
methodology to translate customer emotional feelings into service characteristics. However, it lacks of the knowledge of which service attributes are important and urgent to be taken care of.
Hence, to overcome all the defined deficiencies, the
integrative framework of Kansei Engineering, Kano and QFD has been proposed. It is to link the sensitive or urgent customer emotional needs (known as Kansei) with service attributes experience, and to prioritize which service attributes are to be improved taking into account their impact on Kansei.
QFD is to translate customer needs into product or service elements/characteristics. However, it lacks of the specific customer needs (for instance, customer emotional needs/Kansei) and the weighting scale formulation.
With regard to the details of the proposed approach shown in Table 1, the expected contribution of this current study as contrasted to the previous research on Kansei is as follows. The current study will complete the broader application of Kansei Engineering in different service setting, which is logistics services. The use of QFD accompanied by Pareto diagram is expected to explore and consider more practical solutions based on the current best practice improvements.
Following the Introduction section, this paper is organized as follows. There will be literature review, in which there is a review of recent research on KE applied in services. Afterwards, research methodology and framework development are provided. A case study followed by its findings will be discussed in result and discussion section. Then, it will be wrapped up as a conclusion and further recommendation.
Brief Literature Review
Kansei Engineering in services. Referring to Nagamachi [14] and Nagamachi & Lokman [21], research of KE is ranged from physical product to customer service (which is known as Kansei quality management). Essentially, the core benefit gained is the same, which to start and end with customer emotional needs. More specifically, research of KE in services has been introduced and applied into hotel [16; 9], restaurant [19], and even extended into interior design [22]. The same format of KE model is that Kansei has been defined as the function of perceived services. By taking the current issue of sustainability, KE has been extended to tackle today’s problems. The most recent research on KE which incorporates more efficient approach has been addressed, which is known as an extended model of KE, Kano and TRIZ to solve some potential contradictions among solutions [19]. It, then, has been extended to cover sustainability issues that are covering environmental, economical, and social elements. In term of research gap identified, a short summary of KE research on services in the last 6 years, provided in a matrix of author(s) and main concern(s)/tool(s)/method(s) is shown in Table 2.
Table 2. Recent research on Kansei Engineering applied in services
Author(s) Concerns/Tools/Methods
General KE SERVQUAL Kano TRIZ Cultures Sustainability Logistics
Llinares & Page, 2011 [22] √ √
Hartono & Tan, 2011 [16] √ √ √
Hartono, 2012 [20] √ √ √
Rasamoelina et al., 2013 [23] √
Hartono et al., 2013 [24] √ √ √ √ √
Hartono, 2014 [25] √ √ √
Hartono & Raharjo, 2015 [9] √ √ √ √
Chen et al., 2015 [3] √ √
Hartono, 2016a [19] √ √ √ √ √
Hartono, 2016b [26] √ √ √ √ √
Current research √ √ √ √
remark: √ = related
According to what is provided in Table 1, this current research shows a position in which KE may contribute to the field of logistics services (i.e., third party logistics – 3PL) using general KE methodology integrated with SERVQUAL and Kano model. The choice of logistics field is hoped to generate more practical contribution to today’s trend in services.
to perceived services. Those what have been rated as one-dimensional/linear satisfaction or attractive/delighter [27] are quite related to Kansei-based experience [16]. One-dimensional satisfaction provides a linear relationship between product characteristics fulfillment and satisfaction level, whereas attractive satisfaction will be more on latent need which is unspoken need. Once it is fulfilled, it will generate unpredictable satisfaction. Otherwise, it will give normal satisfaction. More specifically, it is beyond usability and satisfaction. It is hoped that the delighted customers will have an emotional bonding with a particular service provider.
SERVQUAL model and logistics services. In this study, the service quality for logistics services is modeled and measured by SERVQUAL (see [2] for details), which consists of 5 dimensions (i.e., tangibles, reliability, responsiveness, empathy, and assurance). SERVQUAL scales will serve as the measurement instrument of perceived and expected services. Basically, logistics service quality is that the overall and comprehensive activities ranging from order receipt to delivery to the customers.
Related to logistics services, one of the most interesting types for research is that home delivery service, as it has been done by Chen et al.[3]. Another interesting type, which is becoming a global trend, is that logistic service provider (known as third party logistics – 3PL). Third party logistics is deemed to be a critical position in the supply chain for international and domestic trading. According to customer point of view, Franceschini & Rafele [28] stated that the logistics services can be measured through lead-time, regularity, reliability, flexibility, preciseness, harmfulness and productivity. In this current research, it is used 3PL which can be scaled and customized to customer needs such as the demand and delivery service requirements. It may cover products/goods, humans, and several forms of services. In other words, this 3PL may go beyond logistics which include value-added activities.
Framework Development and Research Methodology
Framework development. Based on the research background and formulized state of the art of the KE research in services, a research framework of KE incorporating Kano and QFD is developed (as shown in Fig. 1). It starts with the problems faced by particular logistics services company, and then, spans the Kansei (as the response variable) and perceived service attribute performance (functioned as the predictor variable). Concurrently, Kano categorization process is done to filter the one-dimensional and attractive performance (O and A category) which are sensitive to the Kansei. By generating a linear model continued with the calculation of satisfaction score (see [29]), prioritized improvement for particular service attribute(s) is defined. It is, then, wrapped up with how to generate design specification(s) through House of Quality.
Fig. 1. The Framework of KE, Kano and QFD for logistics services
Case study on IT-based application logistics services
A case study on IT-based application supporting logistics services in Surabaya has been taken. It was called XYZ. A hundred fifty seven actual respondents were involved in the study. The subjects were those experiencing services of XYZ with a period of August – October 2016. They were 54% female and 46% male, with a majority of aged 16 – 25 years (55%), followed by 26 – 35 years (27%), 36 – 45 years (14%), and above 45 years (at about 4%). Mostly they were college students (39%), and followed by professionals (31%), entrepreneurs (17%), and the rest were housewives.
Referring to discrepancy between perceived and expected logistics services, service gap has been calculated in each of logistics service attributes (as shown in Table 3). Afterwards, in order to confirm that the gap was significant, the t-test for comparing two sample means has been done. The results of t-test are provided in Table 3 as well. It shows that, in all service attributes, H0 was rejected. It means that, to all logistics service attributes, the perceived service was less than the expected one. The customers felt that what they have received was not met with what they have expected.
Table 3. The statistical test for logistics service gap
No Logistics service attributes Gap* tvalue pvalue < / > α Remark
Tangibles (T)
1 Vehicle type -0.56 -7.733 0.000 <
0.05
H0 rejected 2 Cleanliness of vehicle -0.86 -11.852 0.000 < H0 rejected 3 Driver performance -0.65 -8.664 0.000 < H0 rejected
4 Completeness of driver’s attributes -0.76 -9.390 0.000 < H0 rejected
9 Food receipt -0.66 -8.399 0.000 < H0 rejected
*the difference between perceived and expected service
Perceived logistics services influenced particular Kansei (i.e., emotional satisfaction). In this study, there were 10 Kansei identified, formulized and measured, i.e., helped (mean = 4.09), trusted (mean = 3.93), secured (mean = 3.91), comfortable (mean = 3.85), innovative (mean = 3.83), friendly (mean = 3.79), precise (mean = 3.70), professional (mean = 3.57), prompt (mean = 3.44) and cheap (mean = 3.32). The distribution of perceived Kansei scores is shown in Fig. 2.It shows that Kansei “helped” has the highest perceived score; it means that in general, the customers felt “helped” once they have received logistics services from company XYZ.
Fig. 2. Distribution of perceived Kansei in logistics services
Afterwards, through Kano categorization process, with respect to attractive [A] and one-dimensional [O] categories, those logistics service attributes belong to were identified. They were then connected to significant Kansei through linear model test, and calculated their satisfaction scores. According to Hartono & Tan [16], the importance weight was determined by incorporating the value of satisfaction score, Kano weight [see [29]], and Kansei score. The higher the importance weight, the more important the service attribute is. The result is shown in Table 4.
Table 4. The importance weight of logistics service attributes
*|satisfaction score| = (perceived – expected) x importance level of service **importance weight = |satisfaction score| x Kano weight x Kansei score
Fig. 3. The Pareto chart of logistics service attributes based on importance weight
cancellations), T10 (appearance of foods ordered) and R18 (knowledge of driver for any interesting places). Using a House of Quality (HoQ), some related design specifications (known as metrics) have been formulized, as shown in Figure 4. It shows that the most critical improvement idea was that the provision of modular system for helmet (inside and outside part) for the customer.
Discussion
This study was actually done as the extension of previous research on KE, Kano and QFD applied in services (see [24]). By taking a case on logistics services, this study is hoped to contribute on the efficiency of logistics performance. The field of logistics services becomes a potential niche to explore. There is a huge market for logistics in Indonesia in year 2004 – 2014, and it becomes larger and larger due to the growth of infrastructures and economic development. Moreover, with respect to customer point of view, third-party logistics (3PL) was chosen since this kind of services can add a great value to customers and companies [3].
With regard to the potential development of emotional-based service quality tools and potential needs for 3PL services, this study has been conducted. It proposed a framework of KE, Kano and QFD applied to one of popular IT-based supporting logistics services in Surabaya. Basically, this company provided services on logistics either for foods, documents or passengers.
According to the research findings, it has been shown that the attribute “cleanliness of helmet for company” was the most important one, which had significant correlation with Kansei word “professional, innovative, cheap, and precise”. Given a very limited time, effort, budget or other resources, the company should focus more on the cleanliness of helmet and its supporting facilities in order to gain more customer emotional satisfaction. Though, the Kansei “helped” was of to be the highest rated emotion experienced by the customers. It was influenced by the performance of attribute “web-based application interface”, “appearance of food ordered”, “confirmation for any cancellations”, and “driver traceability”. In other words, in general, the customers felt helped once they were served by the XYZ company.
It is, also, suggested that the modular system for helmet (inside & outside part) was proposed. It was deemed as the most prominent improvement, and then followed by the provision of application software to give comment and rating anonymously, and also the use of application software for confirmation and cancellation.
Conclusion, limitation and further recommendation
Conclusion. This study promotes the major role of human factors, especially Kansei, in influencing the efficiency and effectiveness of logistics service design and development. The integrated model of KE, Kano and QFD provides the understanding of what should be considered and executed by the service manager or provider in improving the services offered, yet still focusing on the prioritized solutions, given very limited resources. In this study, the improvement on helmet system, and the provision of application software for submitting comment and rating, and doing confirmation/cancellation were rated as high priorities.
T
Fig. 4. The simple form of HoQ for IT-based logistics services improvement
Acknowledgement
This study on the model development and its application on logistics services were fully supported by the research grant under the scheme of applied product with a contract number of 22/SP-Lit/LPPM-01/Dikti/FT/V/2017, endorsed by the Directorate of Higher Education, the Ministry of Research, Technology, and Higher Education, Republic of Indonesia. Also, this was partially supported by the Department of Industrial Engineering, University of Surabaya, Indonesia.
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