A Case Study Review of State-of-Art on Kano Model for Research Direction
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A Case Study Review of State-Of-Art on Kano Model for Research Direction
Abstract: Voice of Customer is the important for product development. Product development is a complex task in which a great deal of human physical resources, methods, and tools are involved. One of the well- appreciated models is Kano model for customer needs study for product development. This study is to identify a research gap from existing literature regarding Kano Model. For this reasons, a review of state-of-art is done regarding Kano Model aspect. Keywords: Kano Model; Product development, A Monte Carlo Simulation, Human-Physical Interactions, Probability, Logical Rules; 1. INTRODUCTION Customer needs with producer capacity assessment is essential for product development. The voice of the customer (VoC) and relevant information can be improved the customer satisfaction according to market segmentation (Garibay et al. 2010, Heo et al., 2007, Huiskonen et al.,1998). In this regards, leveraging strategy is essential for product development with respect to the target market segments considering the customer trends (Weck et al., 2005). Product development is an integrated result of design, manufacturing, research and development, and compliance with Voice of Customers (VoC). Product development is considered main challenge to comply among satisfaction, affordability of customer, production rate, technical ability, human error , production cost, shorter reaction time, selling price, organizational complexity and bureaucracy, value chain and competitor of manufacturer in various customer segments (Browing, 2003; Prasad, 2000; Burlikowska and Szewieczek, 2009; Willcox and Wekayama, 2003; Meier and Kroll, 2008; Matt, 2009).Various challenges are raised from different customer segments according to their individual customer needs. In this respect, manufacturers have been following laws of consumer needs (Petro, 2005), customer pain points (Handfield and Steininger, 2005), and attention of changing customer needs by adapting design requirements (Hintersteiner, 2000). Another challenge of product development is to a volatile and diversified market behavior (Cochran et al., 2000) and the demographic and psychographic factors of customers. Thus, VoC, Organizational Aspects, Peripheral Aspects, Methods and Tools are considered appropriately for product development. (Fujita and Matsuo, 2006). Product development society is working for integrating VoC for real product. For instance, Transitional Business Model (TBM) is developed to incorporate the customer needs into the concept generation processes for aerospace product development (Guenov et al., 2006). Data mining techniques are identified for product development by the researchers Jiao et al., 2007. A knowledge management model is developed by Fagerström and Olsson, 2002 for using Soft System Methodology (SSM) and emphasized the need for effective collaboration between main supplier and customers for adding value to a product development process. Identified factors are explained or significantly contributed to successful launch of product development of an innovation by another research group Haapaniemi and Seppanen, 2008. Integrated design knowledge is applied for reuse framework, bringing together elements of best practice reuse, design rationale capture and knowledge- based support in a single coherent framework by Baxter et al., 2007. A formal basis for the creation of an automated reasoning system is also supported for creative engineering design by Sushkov et al., 1995. Mannion and Kaindle, 2008 developed a formal logic-based approach to deal with the VoC in term of product requirement. The start-up technology-based firm's theory (STBFs) is introduced for undertaking their new product development (NPD) the relationship between corporate strategy and NPD process features by Beven, 2007. Sivaloganathan et al., 2000 carried out a study for the effectiveness of systematic and conventional approaches to design. A stepwise procedure based on quantitative life cycle assessment is integrated of environment aspects in product development by Nielsen and Wenzel, 2002. A model is developed for concurrent product and process design. There are various design concepts to evaluate for identify the 'Best' concept with application of fuzzy logic for design evaluation and proposes an integrated decision-making model for design evaluation at developing a computer tool for evaluation process to aid decision-making (Green and Mamtami, 2004). A design structure matrix (DSM) is provided by Browing, 2003 a simple, compact, and visual representation of a complex system that supports innovative solution to decomposition and integration problems for product development. The rapid change of technology has been led to shorter product life cycles for many
products most particularly in consumer electronics. A product definition and customization system (PDCS) is established to meet rapid change of competitive and globalism business climate (Minderhond and Fraser, 2005; Chen et al., 2005). Moreover, an information technology (IT) framework is solved the product development problem through automatic generation of information. The framework is used the concept of information templates or models and a rule based system to generate manufacturing instructions (Dean et al., 2008). But information cannot be summed for decoupled designs and overcome the problem was applied joint probability density function and uniformly distributed design parameters (Frey et al., 2000).Two important issues in configuration product design are considered including requirement configuration and engineering configuration by Shao et al., 2005 . A deliberate business process is involved hundreds of decisions and supported by knowledge and tools for product development, where a new composition of fuzzy relations that is defined by using the drastic product development (Krishnan and Ulrich, 2001; Mizumoto, 1981). The products model is solved two essential problems redundancy of both technical and marketing effort and lack of long term consistency and focused for an approach to managing new products (Meyer, 1992). Reused design is applied by Ong et al., 2008 for product development modeling and analysis and optimization. Off drape and hand off fabrics are applied by Palicska, 2008 for 3D material simulation for garment manufacture. Integrated design of products and their underlying design processes are provided for a systematic fashion, motivating the extension of product life cycle management (PLM) (Panchal et al., 2004). 'Validation Square' is validated by testing its internal consistency based on logic in addition to testing its external relevance based on its usefulness with respect to a purpose (Pedersen et al., 2000). Concept-knowledge (C-K) theory is applied by Hatchuel and Weil, 2003 for innovative design. The development of a framework is incorporated of different models for environmental analysis, with the option of a broader scope that also includes economic and social aspects, thus covering the three pillars of sustainability (Heijungs et al., 2010). The concept of Lean (Womack and Jones, 1996) has influenced the research of VOC and its implementation. The focuses of all activities are turned to customer needs rather than job-at-hand (Oppenheim, 2004). Browning, 2003 recommend that removing one activity or changing its focus as because it is a non-value adding activity does not help improve overall value of a product. Sireli et al., 2007 developed a detailed procedure to integrate Kano model with QFD for simultaneous development of multiple products for designing a weather information system for cockpit. Chen and Chuang, 2008 integrated Kano model with the concept of robust design so that the relative weights of product performance parameters become more meaningful. Li et al., 2008 integrated Kano model to make AHP (Analytical Hierarchy Process) and rough-set based calculations more meaningful. Xu et al., 2009 developed a variant of Kano model called "analytical Kano model" for making optimal tradeoff between customer's satisfaction and producer's capacity. The effectiveness of this model is demonstrated by redesigning a car dashboard. Nevertheless, the empirical studies (Chen and Chuang, 2008; Li et al., 2008; Xu et al., 2009; Sireli et al., 2007) of Kano model are in a sense helpful in materializing the issues that have been emphasized by the holistic frameworks of product development (Womack and Jones ,1996; Fagerström and Olsson, 2002; Browning, 2003; Oppenheim, 2004; Guenov et al., 2006). The above review leads to obtain, process, and determine a set of customer needs correlating the proper levels of satisfaction of targeted customer segments. Kano model is able to identify a set of product attributes satisfying a set of customer needs (Kano et al., 1984; Berger et al., 1993; Matzler and Hinterhuber, 1998; Jiao and Chen, 2006; Kai, 2007). In this regard, the Kano model is one of the choices for compliance customer needs with producer capacity, because Kano model is done to non-linear relationship between product performance and customer satisfaction. Following section is discussed only Kano model oriented review study.
2. A CONCLUSIVE REVIEW ON KANO MODEL
From above section, there are many models for customer needs assessments. One of the Kano model has been appeared into one of the most popular quality models now days since its introduction in 1984. Kano et al., 1984 has been for two aspects of quality such as subjective and objective. Kano's model of attractive quality (Kano et al., 1984) has been taken the researchers of industries for quality product development (Berger et al., 1993; Matzler and Hinterhuber, 1998; Jiao and Chen, 2006; Kai, 2007; Fuchs and Weiermair, 2004). Based on the information from Kano questionnaire, it provides a quantitative approach to observe and follow the change over time (Raharjo et al., 2009). An investigation is done for 3G mobile services perceive on the market (Baek et al., 2009). The major difference in contrast to other wide spread quality models, such as the technical and functional quality model (Gronroos,1984) or the Gap model (Parasuraman et al., 1985), is that Kano's model is based on the assumption of existence of nonlinear and asymmetric relationships between attribute-level performance of products/services and overall customer satisfaction (OCS). The outcome has been reflected potential weakness of traditional questionnaire of Kano model (Au et al., 2006). Baek and Otto, 2009 has been endeavored to categorize key attributes of Mobile services into five qualities Attributes: attractive, one-dimensional, must-be, indifferent and reverse by using three functional and dysfunctional questions for each attribute, i e., satisfied, neutral and dissatisfied. Berger et al., 1993 derived a Kano model for more effective use. A robust design
approach incorporating the Kano model can enhance customer satisfaction and aesthetic product qualities with multiple -criteria characteristics (Chen and Chuang, 2008). Fuzzy approaches can cope between customer requirements (CRs) and design requirement (DRs) of product development (Chen and Ko, 2008) but they are not study regarding generic unknown customer. A Kano and customer knowledge management (CKM) model is introduced for innovative product development (Chen and Su, 2006). A Kano and neural networks model is applied for web personalization (Chang et al., 2009). The result of TRIZ and Kano model is shown that the home life industry is very competitive (Chen et al., 2010). Gap measures are taken between the professor's expectations and students' perceptions of those expectations in an attempt to explore a variety of performance in terms of basic needs, satisfiers and delighters as well as a variety of demographic variables e.g., gender, age, discipline, course level and teaching experience (Emery, 2006) . Lee and Huang, 2009 is considered fuzzy recommended Kano questionnaires functional side of the questionnaire like, must-be and neutral respectively 20%, 50% and 30%; dysfunctional side of the questionnaire livewith and dislike respectively 50% and 50%. Lee and Huang, 2009 has used fuzzy questionnaire to enhance the deficient of typical Kano's two dimensional quality attribution in questionnaire linguistic scale. Li et al., (2009) developed an integrated method of rough set, Kano's model and AHP for rating customer requirements final importance. All quality attribute are not viewed as equally important to customer (Lin et al., 2010). Lee et al., 2008a developed a decision making trial and evaluation laboratory (DEMATEL) to identify the causality of order winners and qualifiers and the extent to which they interact. Lee et al., 2008b is applied fuzzy Kano model for product life cycle management. Zultner and Mazur, 2006 is derived recent developments of Kano model. Moreover, a list of study regarding Kano model is shown in table 1,encompassing authors (column 1), industry (object)or field of research (column 2), the model type (column 3).
Table 1. Research studies and conceptual papers on the Kano Model Author Kano et al. (1984)Berger et al. (1993)Matzler et al. (1996) Sauerwein et al (1996) Vavra (1997) Huiskonen and Pirttila (1998) Matzler and Hinterhuber (1998) Sauerwein (1999) VonDran et al. (1999) Tan et al. (1999) Rust and Oliver (2000) Martensen and Gronholdt (2001) Ting and Chen (2002) Jane and Dominguez (2003a) Rahman (2004) Lilja (2005)Yang (2005) MacDonald et al. (2006) Zultner and Mazur (2006) Chen and Su (2006) Au et al.(2006) Riviere et al. (2006) Emery (2006) Eskildsen and Kristensen (2006) Heo et al. (2007) Rejeb et al. (2008) Lee et al.(2008) Chen and Ko (2008) Chen and Chuang (2008) Chang et al.(2009) Lee and Huang (2009) Raharjo et al. (2009) Li et al.(2009) Slevitch and Oh (2009) Garibay et al.(2010) Xu et al. (2009)Lin et al. (2010) Li et al.(2010) Chen et al.(2010) Ullah and Tamaki (2010) Industry/ Fieldstechnical productstechnical products sports products to delight customer concptual paper on importance grid analysis customer service strategy planning sports products product design optimization web site designIT (web page) delight for customer employee satisfaction services (hypermarket) using regrssion analysis health care bank services focus on customertechnical products kano methods in product decision theory Using in QFD customer knowledge discovery for innovative PD to foot wear design an optimized preference analysis examination of faculty expectation employee satisfaction kano model to physical usability interaction (PUI) to manage innovation project product life management a fuzzy nonlinear modelcomputational approach web personalization fuzzy mode kano model dynamics for multiple product design imprecision of customer requirements attribute performance and CS evaluation of digital library analytical and computational approach a moderated regression approach CR in mature period PI home life industry innovation to simulate unknown customer answer Model type A model of quality (Q) A model of customer requirements (CR) A model of customer satisfaction(CS)A model of customer satisfaction(CS) A model of quality (Q)A model of production A model of customer satisfaction(CS) A model of product design A model of quality (Q)A model of quality (Q) A model of customer satisfaction(CS) A model of quality (Q)A model of quality (Q) A model of customer satisfaction(CS) A model of customer need(CN) A model of quality (Q)A model of quality (Q) A model of customer satisfaction(CS) A model of quality (Q) A model of product development (PD) A model of product design A model of customer satisfaction(CS)A model of customer satisfaction(CS)A model of customer satisfaction(CS) A model of customer need(CN) A model of customer requirements (CR) A model of product development (PD) A model of quality (Q) A model of customer need(CN)A model of customer need(CN) A model of quality (Q) A model of product design A model of product planning A model of customer satisfaction(CS) A model of quality (Q) A model of customer need(CN) A model of quality (Q) A model of product improvement (PI) A model of product design A method of customer need analysis
Martensen and Gronholdt, 2001 tested the Kano model among more than 300 employees, and achieved a very good explanation of employee satisfaction. Matzler et al. 1996 is striving for customer satisfaction. It means understanding and anticipating what customers' wants of the products in the future but do not expect of them. Matzler and Hinterhuber, 1998 have been made product development projects more successful by integrating Kano's model of customer satisfaction into quality function deployment. Raharjo et al., 2009 integrated Kano's model dynamics into QFD for multiple products design. Rejeb et al., 2008 introduced a new methodology based on Kano model for needs evaluation and innovative concepts comparison during the front-end phases of product development. Riviere et al., 2006 considered adaptive preference target to be a methodology which reduces the number of products to be tested while remaining precise in the definition of the ideal product. Sauerwein, 1999 examined the reliability of test-retest, alternative forms and stability of interpretation. The results are supportive for the Kano model. Sauerwein et al. 1996 is provided an evaluation rule for delighting the customer. Sireli et al. 2007 is integrated of Kano's model into QFD for multiple product design in a robust manner. Tan et al., 1999 developed of Innovative Products using Kano's Model and Quality Function Deployment. Wang and Ji, 2010 was increased understanding Customer Needs for product development through quantitative analysis of Kano's Model. Xu et al., 2009 demonstrated Analytical Kano Model can incorporate customer preferences in product design, while leading to an optimal trade between customer's satisfaction and producer's capacity. Yang, 2005, refined Kano's model and its application of I-S model firms for valuable information. As seen from above literature, that researcher yet could not find generic unknown customer evaluation computer system regarding Kano model based. Ullah and Tamaki, 2010 presented a proposition that the respondents of unknown answers might have selected the states randomly from the functional/dysfunctional sides of Kano model. Thus, all states of functional answer (FA) and dysfunctional answer (DFA) of Kano model; Like(L), Must-be(M), Neutral (N),Live-with (Lw), and Dislike(D) are equally likely.
2.1 A Study the Frame of Kano Model to Meet the Research Gap
Kano model of customer satisfaction defines the relationship between product attribute and customer satisfaction and provides five types of product attributes: 1) Must-be, 2) One-dimensional, 3) Attractive, 4) Indifferent, and 5) Reverse, as schematically illustrated Fig.1, and Table 2.
Classification of Customer Needs
High satisfaction (Delighted)
Attractive (A) One-dimensional (O)
Performance fully absent (Dysfunctional) Performance fully present (Functional)
Must be (M)
Low satisfaction (Disgusted)
Fig. 1. Kano Model for Customer Satisfaction
The combination of functional and dysfunctional answers is then used to identify the status of the attribute in term of: 1) Must-be, 2) One-dimensional, 3) Attractive, 4) Indifferent, or 5) Reverse.
Table 2. Five categories of product attributes based on Kano et al. (1984)
Product attributes Attractive
Definition An Attractive attribute leads to a better satisfaction, whereas it is not expected to be in the product.
Recommendations Include a good number of Attractive attributes
A One-dimensional attribute fulfillment helps enhance Include a good number of the satisfaction and vice versa. One-dimensional Must-be A Must-be attribute absence produces absolute Continue Must-be attributes dissatisfaction and its presence does not increase satisfaction Indifferent An Indifferent attribute, that result neither in satisfaction Avoid Indifferent attributes nor dissatisfaction, whether fulfilled or not. as many as possible Reverse A Reverse attribute presence causes dissatisfaction and Avoid Reverse attributes its absence causes satisfaction. All possible combinations of customer answers and the corresponding type of product attribute are summarized in following Table 3.
Table 3. Kano Evaluation
Dysfunctional Like Must?be Neutral Live ?with Dislike Like Q A A A OMust?be R I I I MNeutral R I I I MLive?with R I I I M Dislike R R R R Q A=Attractive, I=Indifferent, M=Must?be, O=One?dimensional, Q=Questionable, and R=Reverse As seen from Table 3, besides the above mentioned five types of attribute in Table 2, there is one more type of attribute called Questionable. This occurs when one selects Like or Dislike from both functional and dysfunctional sides (i.e., when an answer does not make any sense). As mentioned earlier, Kano model is accommodating for integrating the VOC into the succeeding processes of product development. Thus, for the meaningful integration of VOC into the succeeding processes of product development, it is important to follow of recommendation of Table 2. The straight forward relationship is shown table 4 among functional answer (FA), dysfunctional answer (DFA) and Kano evaluation (KE). This table is also exposed a frame among functional answer (FA), dysfunctional answer (DFA) and Kano evaluation (KE). Functional
Table 4. FA, DFA and KE of Kano Model: Separation and Combination Aspect or Kano Rules
Sl 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 (Q) FA Like Like Like Like Like Must-be Must-be Must-be Must-be Must-be Neutral Neutral Neutral Neutral Neutral Live-with Live-with Live-with Live-with Live-with Dislike Dislike Dislike Dislike Dislike DFA Like Must-be Neutral Live-with Dislike Like Must-be Neutral Live-with Dislike Like Must-be Neutral Live-with Dislike Like Must-be Neutral Live-with Dislike Like Must-be Neutral Live-with Dislike Combination of FA and DFA KE Like Like Like Must-be Like Neutral Like Live-with Like Dislike Must-be Like Must-be Must-be Must-be Neutral Must-be Live-with Must-be Dislike Neutral Like Neutral Must-be Neutral Neutral Neutral Live-with Neutral Dislike Live-with Like Live-with Must-be Live-with Neutral Live-with Live-with Live-with Dislike Dislike Like Dislike Must-be Dislike Neutral Dislike Live-with Dislike Dislike Questionable (Q) Attractive (A) Attractive (A) Attractive (A) One-dimensional (O) Reverse ( R) Indifferent (I) Indifferent (I) Indifferent (I) Must-be (M) Reverse ( R) Indifferent (I) Indifferent (I) Indifferent (I) Must-be (M) Reverse ( R) Indifferent (I) Indifferent (I) Indifferent (I) Must-be (M) Reverse ( R) Reverse ( R) Reverse ( R) Reverse ( R) 25 Questionable
Following tables 5 and 6 are derived from table 4.
Table 5. Probability of FA and DFA regarding Kano Model
Events (E) Like (L) Must-be (M) Neutral (N) Live-with (Lw) Dislike (D) Frequency, f 5 5 5 5 5 Probability, Pr (.) 0.20. 20.2 0.20. 2 Cumulative Probability, CPr (.) 0.20. 40.6 0.8 1
Table 6. Probability of KE regarding Kano Model
Events (E) Attractive (A)Indifferent (I) Must-be (M) One-dimensional (O) Questionable (Q) Reverse ( R) Frequency, f 3 9 3 1 2
Probability, Pr (.) 0.120.3 60.120. 040.08
Cumulative Probability, CPr (.) 0.120.4 8 0.6 0.640.7 2
2.2Traditional Use of Kano Model
Figure 2 shows an example of a format of Kano model at a glance. To implement Kano model, a two dimensional questionnaire is prepared for each product attribute. As seen from Fig. 2, a customer (respondent) can to select one of the states out of Like, Must-be, Neutral, Live-with, and Dislike from the functional side stating his/her level of satisfaction, if the attribute is added to the product. The customer also can to select one of the states (out of the same choices) from the dysfunctional side stating his/her level of satisfaction, if the attribute is not added to the product. It is important that Fig. 2 shows the Kano model-based questionnaires distributed among 27 individuals for their opinion. A customer selects "Dislike" from the functional side (your bicycle wheel is triangular shape) and "Livewith" from the dysfunctional side (your bicycle wheel is not triangular shape). This combination is determined Reverse attribute from table 3. However, while responding to Kano questionnaires the respondents are allowed to choose any combination of the answers from functional and dysfunctional sides. The answers may vary a lot because the respondents are driven by demographic factors (age, profession, income, education level, sex, etc.) psychographic factors (attitude, value, life-style, etc.) and so on (Carrillat et al., 2009).
The bicycle has triangular wheels
0 Like Must?be Neutral Live?with Dislike
An Ideal Answer
Functional Answer Functional Answer Like Must-be Neutral Live-with Dislike Dysfunctional Answer Like Must-be Neutral Live-with Dislike
9 8 7 6 5
4 3 2 1 0 Like Must?be Neutral L ve?with i Dislike
Fig.2. A Kano Questionnaire
For example, another case shown in Fig 2, wherein a respondent has chosen "Like" from the functional side and "Livewith" from the dysfunctional side for attribute of bi-cycle wheel triangular shape. This combination makes the underlying attribute an Attractive attribute (see to Table 3). Figure 2 shows for triangular shape wheel are also Attractive. While Attractive attribute for triangular wheel , it is not practical. In Figure 2, another
respondent might choose "Like" from the functional side and "dislike" from the dysfunctional side for head light of bicycle attribute. This makes the attribute (bicycle) a one-dimensional attribute. One-dimensional for triangular wheel is also not consistent. While all majority of answer is concerned Reverse. Therefore, triangular shape bicycle makes Reverse attribute than One-dimensional/attractive. It is concluded that triangular wheel bicycle is Reverse Attribute, it is consistent conclusion.
2.3 Research Directions
A Kano model has been captured capability of the non-linear relationship between product performance and customer satisfaction, while a straightforward frequency based calculation in aggregating the customer answers (Matzler and Hinterhuber, 1998). Up to date literature do not pursue this idea (Raharjo et al.,2009; Lin et al., 2010 ; Sireli et al., 2007; Chen and Ko, 2008 ; Lee et al., 2008; Heo et al., 2009; Lee and Huang ,2009; Li et al., 2009; Xu et al., 2009; Chen and Chuang, 2008; Sakao, 2009). Complex mathematical procedures suggested in this regard wherein both analytical (Xu et al., 2009) and computational intelligence based (Li et al., 2009; Lee and Huang, 2009) approaches are available. All individuals received a Kano questionnaire may not be able to submit their answers because of time pressure or any other practical reasons i.e., lack of interest, understanding etc. As a result, some of the answers remain unknown; it is caused for a great of uncertainty in the analysis. Moreover, sample of the questionnaire is not covered usually whole population. Data collection from whole population is almost impossible for a research group. Besides sample data is not capable to represent the whole population for decision. Consideration of VoC is crucial for the design of product development. However, how to deal with unknown customer opinion is an important question that needs investigations in details. A model can developed from Kano Model to consider uniform vector probability of FA and DFA, which are Like (L), Must-be (M), Neutral (N), Live-with (Lw) and Dislike (D). Moreover, in this regard, Ullah and Tamaki, 2010 concluded a proposition for generic unknown customer evaluation. The proposition is that the respondents of unknown answers might have selected the states randomly from the functional/dysfunctional sides of Kano model. In this case, all states (Like, Must-be, Neutral, Live-with, and Dislike) are equally likely to occur in the simulated answer. In this aspect, a numerical simulation process regarding Kano Model is desired to compute the various answers and finally decide the status of the underlying product attribute. It is done by two ways: (1) this system can to simulate functional (FA) and dysfunctional answers (DFA) independently and then calculate the probability of Kano evaluation (KE) using Monte Carlo Simulation. (2) A system can to simulate the functional (FA) and dysfunctional (DFA) answers for a given Kano evaluation (KE) (Must-be, Attractive, One- dimensional, Indifferent, or Reverse and Questionable) using Monte Carlo Simulation. Therefore, Monte Carlo simulation, probability, random numbers, logical rule of the model are main component for the model adapted with computer. 3. CONCLUSIONS A Kano model can be adapted with computer using Monte Carlo Simulation to determining the product attribute from virtual customers. This model can be framed by the logical rules of computer for customer evaluation regarding product development. 4. REFERENCES
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Biographical notes: Md Mamunur Rashid is a Management Counsellor (Faculty) at Bangladesh Institute of Management, Dhaka since 2004. He has been working in the areas of Product Development, Quality Management System (ISO 9001:2008), Productivity and Competitiveness, Project Management with MS Project-2007 and Industrial Safety Management. He is currently working at Graduate School of Kitami Institute of Technology, Japan since January 2010. He received B.Sc in Mechanical Engineering from Bangladesh Institute of Technology, Rajshahi in 1993, M.Sc in Mechanical Engineering from Bangladesh University of Engineering and Technology, Dhaka in 1996 and MBA from Bangladesh Open University in 2004. He also did PGD in HRM, PGD in Marketing Management and Diploma in Computer Science and Application. Prior to joining Bangladesh Institute of Management he was a Mechanical Engineer at Jamuna Fertilizer Company Limited of BCIC in 1997-2004. His teaches also Productivity, TQM, Project Management related courses in the BBA and MBA level at DIU, BOU. IBAISU, BUBT at Dhaka, Bangladesh as an adjunct faculty. His main research area is customer needs analysis for product development. His is a member of IEB, JSPE, BSME, BSTD, IPM and BCS.
, Research Direction
Description: A Case Study Review of State-of-Art on Kano Model for Research Direction:-= Research and experimental development (R&D) comprise creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of man, culture and society, and the use of this stock of knowledge to devise new applications. The Millennium Development Goals (MDGs) are eight international development goals that were officially established following the Millennium Summit of the United Nations in 2000, following the adoption of the United Nations Millennium Declaration. A performance appraisal (PA), performance review, performance evaluation, (career) development discussion, or employee appraisal is a method by which the job performance of an employee is evaluated. Performance appraisals are a part of career development and consist of regular reviews of employee performance within organizations.