RAW MATERIAL SUPPLIER SELECTION’S FACTORS FOR HORECA BUSINESSES

by

T. WasusriLogistics Management Program,

Graduate School of Management and InnovationKing Mongkut’s University of Technology Thonburi,

Bangkok, 10140, Thailand Email : thananya.was@kmutt.ac.th, twasusri@gmail.com

and

C. Kulwitit 126 Prachautid Rd., Bangmod, Tungkru, Bangkok, 10140, Thailand

Tel: +662-470-9790, Fax : +662-470-9798

ABSTRACT

Nowadays, entrepreneurs concentrate on differentiation in products and services. At the same time, cost is oneof competitive advantages that is needed to manage. It can be seen that many entrepreneurs realize benefits from outsourcing in terms of raw materials, semi-finished products and logistics services. Those outsource activities could be a component in manufacturing or service sectors. In Food sectors, they see the important of outsourcing raw materials for serving its customers. Horeca is a sector of the food sector as serving food and beverages is one of their main services. From characteristics of raw materials required by HoReCa businesses, suppliers must select a variety of raw materials to serve HoReCa customers including delivery service at customers’ place. To increase or maintain competitiveness, food service businesses need to understand HoReCa businesses’ expectation in order to continuouslyimprove on their services. This research is to develop an assessment system for the food service industry by using SERVQUAL. We gathered 100 questionnaires from HoReCa businesses and analyze them by using a factory analysis to group indices that HoReCa businesses determined to be important factors that can be used to select or assess food service businesses. We found that 17 incides could be grouped and we called this group as the heart of HoReCa.

KEYWORDSHoReCa, SERVQUAL, Food Service, Supplier Selection

INTRODUCTION

Nowadays, entrepreneurs concentrate on differentiation in products and services and at the same time, cost is cost is one of competitive advantages that is needed to manage. It can be seen that many entrepreneurs realize benefits from outsourcing in terms of raw materials, semi-finished products and logistics services. Those outsource activities could be a component in manufacturing or service sectors. In Food sectors, they see opportunities on supplying fresh raw materials to serve ‘HoReCa’. HoReCa is an abbreviation of the words Hotel, Restaurant and Café and the HoReCa businesses grow very fast in recent years.

Serving excellent food and beverages is the main target of HoReCa busiensses. The food service industry then realizes the needs of HoReCa businesses that would need to have excellent fresh raw materials to cook and serve for their own customers. The food service industry is working like a moveable supermarket that provides fresh vegetable, fresh meat and also ingredients to HoReca businesses.

From characteristics of raw materials required by HoReCa businesses, suppliers must select a variety of raw materials including delivery service at customers’ places. To increase or maintain competitiveness, food service businesses need to understand HoReCa businesses’ expectation in order to continuously improve their service quality. This research is then to identify the factors or indices that HoReCa businesses determine to be important and can be used as assessment criteria to select a food service provider.

LITERATURE REVIEW

Service quality

Krajewski and Ritzman (2005) said that processes are the fundamental activities that organizations use to do work and achieve their goal. A process is consisting of any activity or group of activates that takes one or more inputs transforms and adds value to them and provides one or more outputs for the customers. Services are processes and performances (Zeithaml and Bitner, 2003). Moreover, Fitzsimmons and Fitzsimmons (2004) noted that in terms of service, the process is the product. Service process is then different from manufacturing process because it possesses some distinctive characteristics of service operations that are customer participation in the service process, simultaneity; perish ability, intangibility and heterogeneity. While Locklove (1983) classifies services on the nature of the service. Tangible and intangible actions towards people or things are distinguished. Schmenner (1986) classifies services by proposing a service process matrix in Figure 1. In this matrix, services are classified into two dimensions that significantly affect the character of the service delivery process. The vertical dimension measures the degree of labor intensity. The horizontal dimension measures the degree of customer interaction and customization on the provider’s processes. Little interaction between customers and service providers is needed when the service is standardized rather than customized. The four quadrants of the service process matrix have been given names as defined by the two dimensions to describe the nature of the services illustrated. The service factory provides a standardized service with high capital investment and it is much like a line-flow manufacturing plant. Service shops permit more service customization, but they do so in a high –capital environment. Customers of a mass service will receive an undifferentiated service in a labor-intensive environment, but those seeking a professional service will be given individual attention by highly trained specialists.

FIGURE 1 SERVICE PROCESS MATRIX

SERVICE SHOP

Hospitals Auto Repair Other repair services

SERVICE FACTORY

Airlines Trucking Hotel Resort and receration

PROFESSIONAL SERVICE

Physicians Lawyers Accountants Architects

MASS SERVICE

Retailing Wholesaling Schools Retail aspects of commercial banking

LOW HIGH

LOW

HIGH

Degree of interaction and customization

Deg

ree

of

lab

or

Inte

nsi

ty

Source: Schmenner (1986)

Regardless of services category, the service provider share similar challenge. Services with capital intensiverequire close monitoring of technological advances to remain competitive. This high capital investment also requires managers to schedule demand to maintain utilization of the equipment. While managers of highly labor intensive services must concentrate on human resource management. The degree of customization affects the ability to control the quality of service being delivered and the perception of the service by the customer (Schmenner, 1986).

Additionally, challenges is not restricted only service managing, but also the way of measuring its quality. Measuring service quality is challenge because customer satisfaction is determined by many intangible factors. Service quality often extends beyond the immediate encounter because it has an impact on a person’s future quality of life(Fitzsimmons and Fitzsimmons, 2004).

Service quality is considered as a complex construct and, it generates many debates regarding its conceptualization and measurement, causing confusion among researcher and practitioner (Ekinci, 2002).

Measuring service quality

Service is usually the result of the interaction between the customer and the service system, including the contact staff, equipment, service environment and facilities. It is the interaction that results in the characteristics of service which make the provision, measurement and control of quality difficult (Silvestro et al., 1990).

Levis (1995) notes three areas of difficulty in measuring service quality that are methodological problems relating to the service quality dimensions, variations in customer expectations, and the nature of the measurement tools. Hence measurement of service can be done in either hard or soft methods. Hard measures are quantifiable or objective. Soft measures are those which are qualitative, judgmental, and subjective and based on perceptual data (Silvestro et al. ,1990).

Because of this difficulty, there are many debates and models of service quality measurement during past few years. Each service measurement model depends very much upon how the researcher view and define service quality which causes different in handling service quality issues (Ekinci, 2002; Davies et al., 1999; Robinson, 1999).

Parasuraman et al. (1990) define service quality from a comparison of expectation with performance perception. Teas (1993) views service quality derives from a comparison of performance with ideal standards. Cronin and Taylor (1992) view service quality derive from perception of performance alone.

Although there are several debates over service quality definition, but all researchers share common ground as follows: (Robinson, 1999)a) service quality is an attitude and it is distinct from customer satisfaction b) perceptions of performance need to be measuredc) the number and definition of dimensions depends on the service context andd) negatively worded statement should be avoid unless the survey is ‘short’ e)

Since the subject of service quality is very rich in context of definitions, models and measurement issue. Several researchers explored the subjects with varying perspectives and using different methodologies (Silvestro et al., 1990).With these issues, only the model for conventional services will be presented on this literature:

a) Technical and functional quality model (Ekinci, 2002; Seth et al., 2005)b) Gap Model (Parasuraman et al., 1985 ; Parasuraman et al., 1990)c) Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) (Hwang and Yoon, 1981; Lai et al., 1994;

Yoon and Hwang, 1995)d) Attribute Service Quality Model (Haywood-Farmer, 1988)e) Synthesized model of service quality (Brogowicz et al., 1990)f) Performance Only Model (Cronin and Taylor,1992; Cronin and Taylor, 1994),g) Ideal value model of service quality (Mattsson, 1992)h) Evaluated performance and normed quality model (Teas, 1993)i) Model of perceived service quality and satisfaction (Sprengand Mackoy, 1996)]j) PCP attribute model (Philip and Hazlett ,1997) k) Retail Service quality and perceived value model (Sweeney et al., 1997)l) Service Quality, Customer Value and customer Satisfaction Model (Oh, 1999)

It can be noted that even though there are several service quality measurement models, but all of them are rooted from the three definitions of service quality and same common area. Among service quality measurement model, SERVQUAL are more mature and gain popular among services research. We then apply SERVQUAL to assess quality of food service providers.

METHODOLOGY

From the literature review, there are a lot of service quality assessment model which depends on how the researcher defines service quality. On this study, SERVQUAL is utilized because it is easy to use, analyse and understand. SERVQUAL can help service manager to identify and focus on service process issues. Moreover, this model has been developed to measure service quality across various environments.

Although SERVQUAL tend to be universal model for measuring service quality across industry, there is a concern regarding the reliability of comparing service expectations from a general industry sector with the actual service quality perception of a particular company. Expectation and perception may not be correlated and can cause varying

result from different respondents. A possible solution to the problem is to design each SERVQUAL study to the particular company or industry under investigation (Francheschini and Rafele, 2000).

To design SERVQUAL, measurement indices are collected from various sources, including SERVQUAL’s universal indices. We used five key words from SERVQUAL that are tangibles, reliability, responsiveness, assurance, and empathy to produce indicators regarding those key words. We then sent out those indicators to 3 experts that are a lecturer, a chef and a purchasing manager to evaluate the appropriate of the indicators. The indices were examined by the experts by using content validation method whether the content of indices is appropriate for measuring service quality in HoReCa businesses. This is to seek for comment from the experts whether the content of indices is relating to the objective of research by asking the expert to score the degree of relationship within the range of +/-1.

C1 = -1 means the contents of the indices is not related to the objective of researchC1 = 0 means the contents of the indices is ambiguous against objective of researchC1 = 1 means the contents of the indices is related to objective of research and can be used to measure quality of service.

The result from each expert will be further processed to find the ‘index of Item Objective Congruence (IOC)’. To complete IOC, it is compulsory that the result must be from at least 3 experts, otherwise it is impossible to calculate the idea of majority and IOC can be calculated as shown equation 1:

N

cIOC

N

ni

1 (1)

where

IOC = Index of Item Objective CongruenceCi = score of comment from expertN = Number of expert

If 0.05 ≤ IOC ≤ 1.00 means Index of Item Objective Congruence is acceptable.If IOC < 0.05 means Index of Item Objective Congruence is not suitable and should be withdrawn.

After receiving the responses from the experts, the questionnaires were modified and there are 51 indices included. The samples are hotels, restaurants or cafes. The respondents would be purchasing managers, chefs or the businesses’ owners who are authorized to select food service providers. As we would like to identify the criteria or expectation on food service providers and the perception from their food service providers, we would then apply a factor analysis. Comrey and Lee (1992) propose sample sizes for conducting a factor analysis as shown in table 1. We distributed 300 questionnaires to our target group. However, 100 questionnaires were sent back. The response rate is only 33.33%

TABLE 1 THE SAMPLE SIZES AND THEIR FITNESS FOR FACTOR ANALYSIS

Sample Sizes Fitness for Analysis50 Very poor

100 Poor200 Fair300 Good500 Very good

1000+ Excellent

Although we could receive only 100 questionnaires, we analyzed the data by using the Kaiser-Meyer-Olkin measure (KMO) to measure sampling adequacy. KMO is an index for comparing the magnitudes of the observed correlation coefficients to the magnitudes of the partial correlation coefficients. Large values for the KMO measure indicate that a factor analysis of the variables is a good idea. KMO of the expectation data is 0.81 and it is good to conduct a factor analysis. The KMO analysis is shown on table 2.

TABLE 2 KMO AND BARTLETT’S TEST

RESULTS

From the data, we applied a factory analysis in order to group indices into components or factors that are related. Then, we could analyze on the factors that are of interest by HoReCa businesses effectively. Firstly, we extracted factors by using a principal component analysis (PCA) to identify variances of factors as shown in table 3. It can be seen from the table 3 that Eigen values decrease very quickly from component 1 to component 2. We then grouped the indices into 7 components or factors by cutting off factors in which Eigen values are less than 1. Acomponent matrix has then been done and it was followed by a factor rotation by a varimax technique. A part of the component matrix is shown in table 4.

TABLE 3 THE COMPONENT MATRIX

Component Initial Eigen values Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings

Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

1 30.569 59.939 59.939 30.569 59.939 59.939 10.000 19.609 19.609

2 2.509 4.920 64.859 2.509 4.920 64.859 9.062 17.768 37.377

3 1.947 3.818 68.677 1.947 3.818 68.677 7.650 15.000 52.376

4 1.714 3.360 72.037 1.714 3.360 72.037 4.314 8.459 60.835

5 1.405 2.755 74.792 1.405 2.755 74.792 3.994 7.831 68.667

6 1.139 2.234 77.026 1.139 2.234 77.026 3.169 6.214 74.881

7 1.019 1.998 79.024 1.019 1.998 79.024 2.113 4.143 79.024

8 .879 1.724 80.748

9 .837 1.640 82.388

10 .748 1.467 83.856

Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.810Bartlett’s Test of Approx. Chi-Square Sphericity 7.671E3

df 1275Sig. 0.0000

TABLE 4COMPONENT MATRIX

Component

Indices 1 2 3 4 5 6 7

Clean and new trucks and handling equipments

.877 .212

Reliability on products and services .867 -.309

Price .850 -.262

Right quantity .843 -.377

Confirming on delivery appointment .829

On time delivery .825 -.262

Quick response .821 -.261

Details of product and service .821 -.264

Concerning on solving problems .820

Right quality .818 -.361

We did a varimax matrix to screen important indices in order to identify ‘the heart of HoReCa business’. Table 5 shows indices that have been weighted to be very important indices. Seventeen indices were grouped as a component that HoReCa businesses could use it to evaluate their suppliers. Right quality, right quantity and traceability are the top three factors for HoReCa businesses.

TABLE 5ROTATED COMPONENT MATRIX

ComponentIndices

1 2 3 4 5 6 7

Right quality .770 .271 .323 .224

Right quantity .764 .318 .255 .219

Traceability on products and service .762 .220 .210 .263 .245

Concerning on solving problems .741 .289 .326 .239

On time delivery .707 .286 .285 .292

Right price .679 .395 .299 .275

Having a delivery schedule .674 .401 .285 .278

Quick response on claims .650 .218 .446 .207 .276

Having an exact time for ordering .620 .488 .348

Details of product and service .591 .470 .322 .230 .317

Having continuous improvement .564 .419 .279 .282 .206 .221

Publishing selling prices .529 .437 .282 .336 .243

Consistency on hospitality .517 .295 .375 .352 .466

Having confirmation system on delivery time

.473 .330 .446 .257 .324

Welcome on suggestions .471 .318 .464 .381 .281

Sales person interests on customer needs/problems

.473 .330 .446 .257 .324

Staff taking carefully on delivery processes

.471 .318 .464 .381 .281

CONCLUSION AND DISCUSSION

From our study, we could identify ‘the heart of food service providers for HoReCa’ by using a factory analysis. The most important factor is food quality. It means that food safety and food quality cannot compromise. Certifications regarding to food quality and food safety such as GMP and HACCP can be said as an order qualifier. The second important factor is quantity. Then, an order fulfillment process of the food service providers have to be punctuality and it is followed by traceability in order to trace back on their raw materials to correct or solve when non-conforming products are occurred. On time delivery is a need of HoReCa businesses. A delivery time schedule must be confirmed and the service providers must follow the schedule exactly. Quick response on following up complains or changing products is one more competency that HoReCa businesses consider as an important factor. If they do not take this performance into account, their suppliers will never improve. Moreover, suggestions on selecting perfect raw materials for some special menus are preferable. The suggestions from the service providers can imply as a supplier helping it customers on developing a new product.

To meet with the heart of food service providers’ factors, there are three action plans needed to implement. Firstly, a food quality management plan, food service providers have to set long term and short term plans regarding to food quality standards. HACCP, GMP, ISO 9000 cannot be missed out. As those standards could improve management systems and good products are results from a good management system. Secondly, a logistics and supply chain management plan is very crucial for today businesses. On time delivery with lower logistics cost is a competitive advantage for businesses. Implementing logistics and supply chain management could increase their efficiency and reduce costs at the same time. Finally, developing people are very essential for service businesses. A good human resource management must be implemented in order to make sure that every staff could understand the company’s mission and vision. Continuous improvement programs for staff are supported. Staff must be service minds as customers are involved all the process in the service industry.

REFERENCES

Brogowicz, A., Delene, L. and Lyth, D. A, (1990). “Synthesised Service Quality Model with Managerial Implications”, International Journal Of Service Industry Management, Vol. 1 No.1, pp 27-45.

Comrey, A. L., and Lee, H. B. (1992), A First Course in Factor Analysis,2nd Ed., New Jersey, Lawrence Erlbaum Associates.

Cronin,J.J. and Taylor, S.A. (1992), “Measuring service quality: a reexamination and extension”, Journal of Marketing, Vol.56, pp. 55-68.

Cronin, J.J. and Taylor, S.A. (1994). “SERVPERF versus SERVQUAL: reconciling performance-based and perception-minus-expectations measurement of service quality”, Journal of Marketing, Vol. 58 No. 1, pp. 125-31.

EKinci, Y. (2002). “A Review of Theoretical Debates on The Measurement of Service Quality: Implication of Hospitality Research”, Journal of Hospitality & Tourism Research, Vol. 26, No.3, pp’199-216.

Davies, B., Baron, S., Gear, T., and Read, M. (1999), “Measuring and Managing Service Quality”, Marketing Intelligence & Planning, Vol. 17, No.1, pp.33-40.

Fitzsimmons, J.A., Fitzsimmons, M.J. (2004), Service Management : operations, strategy and information technology, New York, NY: McGraw-Hill.

Franceschini F., and Rafele C. (2000), “Quality Evaluation in Logistics Services”, International Journal of Agile Management Systems, Vol.2/1, pp.49-53.

Haywood-Farmer, J. (1988), “A Conceptual Model of Service Quality'', International Journal of Operations and Production Management, Vol. 8 No. 6, pp. 19-29.

Krajewski, L.J., and Ritzman, L.P. (2005), “Operations Management”, pp.3-4. New Jersey, Peason Education.

Lovelock, C. (1983), “Classifying services to gain strategic marketing insights”, Journal of Marketing, Vol.47, No.3, pp. 9-20.

Levis, B. (1995), “Customer Care in Services”, in Davies, B., Baron, S., Gear, T., and Read, M. (1999), “Measuring and Managing Service Quality”, marketing Intelligence & Planning, Vol.17, No.1, pp’33-40.

Mattsson, J. (1992), “A service quality model based on ideal value standard”, International Journal of Service Industry Management, Vol. 3 No. 3, pp. 18-33.

Oh, H. (1999), “Service quality, customer satisfaction and customer value: a holistic perspective”, International Journal of Hospitality Management, Vol. 18, pp. 67-82.

Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1985), “A Conceptual Model of Service Quality and Its Implications For Future Research”, Journal of Marketing, Vol. 49 No. 3, pp. 41-50.

Parasuraman, A., Zeithaml, V.A., and Berry, L.L. (1990), “Delivering Quality Service-Balancing Customer Perception and Expectation”, New York, The Free Press.

Philip G. and Hazlett S-A. (1997), “The Measurement of Service Quality: a New P-C-P Attributes Model”, International Journal of Quality & Reliability Management, Vol. 14, No. 3, pp. 260-286.

Schmenner, R.W. (1986), “How Can Service Business Survive and Prosper?”, Sloan Management Review, Vol 27, No.3 pp.25.

Seth, N., Deshmukh, S.G., and Vrat, P. (2005), “Service Quality Models; a review”, International Journal of Quality and Reliability Management, Vol.22, No.9, pp.913-949.

Silvestro, R., Johnston, R., Fitzgerald, L., and Voss, C. (1990), “Quality Measurement in Service Industries”, International Journal of Service Industry Management, Vol.1, Issue 2.

Spreng, R.A. and Mackoy, R.D. (1996), “An empirical examination of a model of perceived service quality and satisfaction”, Journal of retailing, Vol. 722, pp. 201-14.

Sweeney,J.C., Soutar, G.J., Johnson, L.W. (1997), “Retail service quality and perceived value : A comparison of two models, Journal of Retailing and Consumer Services”, Vol. 4, Issue 1, pp. 39-48

Teas, R.K. (1993), “Expectation, Performance evaluation, and consumers’ perception of quality”, Journal of Marketing, Vol 57 No.5, pp.18-34

Hwang, C.L., and Yoon, K. (1981). “Multiple Attribute Decision Making: Methods and Applications”, New York, Springer-Verlag.

Lai, Y.J., Liu, T.Y. and Hwang, C.L. (1994). “TOPSIS for MODM”, European Journal of Operational Research 76 (3), pp. 486-500.

Yoon, K., and Hwang, C.L. (1995), “Multiple Attribute Decision Making: An Introduction”, Thousand Oaks, CA., Sage

Zeithaml, V.A., Bitner, M.J. (2003), “Service Marketing : Integrating Customer Focus Across the Firm”, 3rd Edition,New York, NY : McGraw-Hill.