CHAPTER 4 – RESEARCH METHODOLOGY
4.1 Proposed Research Methodology
4.1.2 Data Collection
customers and suppliers. Due to the enormous business opportunity presented by exhibitions, many countries are dedicated to investing in and developing the exhibition industry. According to ICCA (International Congress & Convention Association), there are about 40 thousand exhibitions held each year across the world, costing a total of about 28 billion dollars. UFI (The Global Association of the Exhibition Industry) also indicates that the output value of the exhibition industry is approximately 160 billion dollars. In view of the importance and the benefits of the exhibition industry, the Service Science Research Center (SSRC) in National Chengchi University (NCCU) conducted a project that endeavored to build an innovative mobile service named ―Orbi‖ for exhibition use. The functions of Orbi are summarized in Table 4.2. The goal of Orbi was to streamline the exhibition process and allow exhibitors and visitors to match and interact efficiently. To collect the data, we distributed a survey at a professional exhibition ―TaiSPO‖ held at the Taipei World Trade Center Nangang Exhibition Hall in April 2010. 2010TaiSPO was the 37th exhibition held for promoting Taiwanese athletic products, an industry that generates about 60 billion dollars every year. The exhibition attracts hundreds of exhibitors and thousands of buyers, thus becoming the most important athletic goods purchasing exhibition in Asia. The questionnaire was designed as a paper-based and PDF-based survey (Appendix A). Visitors and buyers were required to finish the questionnaire when returning the Orbi device. Over the course of the three-day exhibition, we collected 105 questionnaires that included 54 international buyers and 51 visitors, as shown in Table 4.3. Of these questionnaires, 98 were found to be complete and usable.
Table 4-2. The Mobility Classification and Functions of Orbi
Function Description spatial
mobility
The WLAN GPS-powered Map application points you to the right direction on the map and helps you find booth locations accurately and quickly. Map on Orbi provides short cuts to access other applications.
It also combines other useful tools you might need.
HIGH HIGH LOW
‧
designed for the exhibition safari. Use it to browse a list of all exhibitors and obtain more details. Fast!LOW LOW LOW
Products
Orbi features Products — a useful application designed for the exhibition safari. Use it to browse a list of all products and obtain more details. Fast!
LOW LOW LOW
Activity
Orbi automatically informs you of upcoming events you might be interested in, so that you will not miss any opportunity to network and build relationships with suppliers. Moreover, Orbi allows you to browse a list of exhibition activities and shows you the venues of the events on its display screen.
HIGH HIGH HIGH
Express
Discover Orbi intelligence. If you are embarking on an exhibition journey to service excellence, let Express be your guide. No other business trade show tool does it like Orbi.
HIGH HIGH HIGH
Collection
Orbi makes it easy for you to keep all exhibitors and product marketing materials. Click the Collect It button on the Exhibitor, Product, or Activity pages.
Moreover, Orbi allows you to review collected information whenever and wherever you are.
LOW LOW LOW
Quick note
Orbi enables you to simultaneously keep records and take notes right there in the exhibition hall. You don't have to wait until you have access to a PC to keep notes. Orbi also provides practical indicators to help you evaluate exhibitors. Simply tap and score on the touch screen.
LOW LOW LOW
Search
Orbi’s innovative intelligence service platform predicts and suggests keywords as you search information for the entire exhibition in a whole new way.
HIGH LOW HIGH
Information You can browse through a wide range of information
related to transportation, food, shops, and more. LOW LOW LOW
‧
exhibitor’s information. Tap the Map button to show you the location of an exhibitor.LOW HIGH LOW
Recommend
If you are looking for a new exhibitor or product, try Orbi recommendations. Just tap the Recommendation button to see a list of exhibitors or products you might be interested in based on the comments of other like-minded exhibition visitors.
HIGH LOW HIGH
Table 4-3. Characteristics of the Study Sample Characteristics of the Respondents
International Buyers Local Buyers Visitors
22% 30% 48%
Positions of the Respondents
President/Chairman 20% Analyst 3%
Manager 26% Specialist 9%
Designer 2% Consultant 7%
Executive/Director 18% Others 15%
Industry Group
Retail sales enterprises 3%
Fitness equipment industry 11%
Sports industry 20%
Rubber products industry 3%
Textile industry 8%
Government institutions 8%
Machinery and equipment manufacturing 10%
Computer and peripherals industry 5%
Educational institution 19%
Consulting industry 9%
Medical industry 4%
‧
We chose a Partial Least Squares (PLS) approach for the data analysis because of its minimal requirements for measurement scales and sample size (Chin et al., 1998).
Chin et al. also pointed out that reflective and formative relation could be specified in PLS. We followed the criteria of distinguishing between formative and reflective indicators provided by Jarvis et al. (2003) to model the service performance as a formative construct because the items within the construct were not interchangeable and covaried with each other. Individual differences were modeled as reflective constructs because all the items of each construct reflected the same underlying construct and were interchangeable. We first conducted the item reliability and the validity examination. Item reliability analysis provided the information about the consistency, stability, and internal consistency of the data. We identified the reliability by examining the loadings and composite reliability. Bagozzi and Yi (1988) have suggested that the loadings of items within each construct should exceed 0.5 and the composite reliability of each construct should exceed 0.6 to ensure internal consistency. All of the constructs were above the suggested value that demonstrates the satisfactory internal consistency (see Table 4-4).
We considered the convergent validity and discriminant validity in order to measure the construct validity (which means that the questionnaire accurately reflected the respondent’s reaction). Fornell and Larcker (1981) concluded that the average variance extracted (AVE) of the constructs should be greater than 0.5 to ensure the convergent validity. Chin et al. (1998) has suggested examining the discriminant validity by identifying the cross-loading matrix and the square root of AVE. All of the
Table 4-4. Item reliability Analysis (n=98)
Factor Item Mean S.D. Loadings Reliability AVE