1. SCALE DEVELOPMENT ON CONSUMER BEHAVIOR TOWARD COUNTERFEIT DRUGS IN A DEVELOPING COUNTRY SETTING Alfadl, Abubakr Abdelraouf (1); Ibrahim, Mohamed Izham (2); Hassali, Mohamed Azmi (1) 1: Universiti Sains Malaysia, Malaysia; 2: Qassim University, Saudi Arabia, Universiti Sains Malaysia, Malaysia SCALE DEVELOPMENT ON CONSUMER BEHAVIOR TOWARD COUNTERFEIT DRUGS IN A DEVELOPING COUNTRY SETTING Alfadl, Abubakr Abdelraouf (1); Ibrahim, Mohamed Izham (2); Hassali, Mohamed Azmi (1) 1: Universiti Sains Malaysia, Malaysia; 2: Qassim University, Saudi Arabia, Universiti Sains Malaysia, Malaysia Ajzen, I. & Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behavior. Englewood Cliffs, NJ: Prentice Hall. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. Churchill, G. (1979). A Paradigm for constructing better measures of marketing concept. Journal of Marketing Research, 16(1), 64-73. De Vellis, R. F. (1991). Scale development: Theory and applications. Newbury Park, CA: Sage. Zaichkowsky, J. L. (1985). Measuring the involvement construct. The Journal of Consumer Research, 12(3), 341-352. Conclusion References Introduction: Counterfeiting of medicines in developing countries has been reported as a distressing issue. Moreover, although desperate need and drug counterfeiting are linked, no much study has been carried out to cover this area, and there is a lack of proper tool and methodology. Objective: The objective of this research is to develop a valid and reliable scale based on the currently accepted scale development paradigm to operationalize the main construct. Design, Study Settings and Population: This is a quantitative survey conducted in Sudan through two rounds; pilot (n = 100), and final survey (n = 1003). Sampling approach was based on the availability of participants. Results: The raw data were analyzed using SPSS version 16. Internal consistency was examined and improved. Cronbach’s alpha improved from 0.818 to 0.862. Finally, convergent and discriminant validity was demonstrated. Conclusion: To the authors’ knowledge, this is the first work attempt to conceptualize and operationalize consumer behavior toward counterfeit drugs. High reliability and demonstration of convergent and discriminant validity indicated that the “Consumer Behavior toward Counterfeit Drugs Scale” is a valid, reliable scale existing within a solid theoretical base. Ultimately, the study offer public health policy makers and marketing manager a valid measurement tool to build a better understanding of the demand side of counterfeit drugs and hence aids in developing more effective strategies to combat the problem. Keywords: Counterfeit drug, Consumer, Behavior, Scale This research aims at establishing the necessary knowledge of the demand side of the problem of counterfeit drugs. In other words, this research aims at providing a better understanding of vulnerability to counterfeit drugs, which, in this context, are to be understood as the major characteristics, derivers, and influencing factors of demand with respect to counterfeit drugs. Specific objective of this research is to propose a conceptual framework based on Theory of Planned Behavior (TPB) (Ajzen, 1991) and Theory of Reasoned Action (TORA) (Ajzen & Fishbein, 1980) to develop a valid and reliable scale based on the currently accepted scale development paradigm to operationalize the main construct. Although desperate need and drug counterfeiting are linked in developing countries, no much research has been carried out to address this area, and there is a lack of proper tool and methodology. This study addresses the need for a scale to aid in understanding demand side of drugs counterfeiting. As this research prime focus is developing a scale to measure consumer behavior regarding counterfeit drugs purchase and factors influencing this behavior, it seems that Theory of Planned Behavior (TPB) (Ajzen, 1991) with its roots in Theory of Reasoned Action (TORA) (Ajzen & Fishbein, 1980) is a suitable conceptual framework (Figure 1). It was also suggested that it is suitable to develop the scale following the procedures advocated by Churchill (1979) and DeVellis (2003) (Figure 2).. Price quality inference (PQ) Perceived risk (PR) Risk averseness (RA) Product attributes (PA) Awareness of societal consequences (ASC) Subjective Norm Attitude Toward Counterfeit Drugs Purchase Accessibility (Ac) Availability (Av) Affordability (Af) Motivation to Purchase Counterfeit Drugs Intention to Purchase Counterfeit Drugs Normative Beliefs and Motivation to Comply Phase 1: Items generation and reduction In this study, decision rule that focused on the overall evaluation of all the judges was used Zaichkowsky’s (1985). The application of this judging procedure reduced the number of items across the four aspects from sixty nine items to forty four items. Data Analysis of the First and Second Round of Data Collection The two samples covered all age groups from 18 to 75 years. They contained 52% and 47% males for the first and second samples respectively. Respondents reported their annual income in five groups, their education status in four groups, and their working status in ten groups. Step 1: Domain Specification  Literature Search Step 2: Item Pool Generation  Literature Search  Experts Step 3: Expert Item Judging  Item Relevance  Item Clarity  item Conciseness  Reviewers Suggestions Step 4: Data Collection Step 5: Measure Purification Step 6: Data Collection Step 7: Dimensionality Assessment Step 8: Reliability & Validity Assessment  Coefficient Alphas  Exploratory Factor Analysis Step 9: Norms Development  Exploratory Factor Analysis  Coefficient Alpha & Average Variance Explained  Convergent Validity  Discriminant Validity  Average and Other Statistics  Summarizing Distribution of Scores First sample Cronbach’s alpha was determined for each of the dimensions suggested by the conceptual framework to provide a preliminary assessment of reliability. An examination of the item-to-total correlations within each dimension was conducted. Based on item-to-total correlations two items from perceived product attribute dimension and one item from perceived risks dimension were deleted. Cronbach’s alpha for the complete 41 item scale improved from 0.818 to 0.862. Scale items were then assessed by examining means, variances, squared multiple correlations (SMCs), item-to-total correlations and result of an exploratory factor analysis (EFA) using component factor analysis with varimax rotation. The initial EFA on all 41 items disclosed a thirteen factor structure. Three items failed to load significantly (≤.5) on any factor. Other two items loaded on more than one factor (i.e., cross-loaded). Consequently, an iterative process conducted where by the authors removed scale items one at a time which stopped when the analysis exhibited a clean factor structure (i.e., no non-loading items, no cross- loading items). Second sample Convergent validity was tested through evaluating average variance explained (AVE) and reliability estimates (Cronbach’s alpha). All AVE exceed.5, while all reliability estimates are well above.60. Secondly, discriminant validity was assessed through comparing individual bivariate correlation matrix and the reliability estimates. No correlation is higher than the reliability estimate. To the authors’ knowledge, this is the first work attempt to conceptualize and operationalize consumer behavior toward counterfeit drugs. High reliability and demonstration of convergent and discriminant validity indicated that the “Consumer Behavior toward Counterfeit Drugs Scale” is a valid, reliable scale existing within a solid theoretical base. Ultimately, the study offer public health policy makers and marketing manager a valid measurement tool to build a better understanding of the demand side of counterfeit drugs and hence aids in developing more effective strategies to combat the problem. Scale and Reliability Statistics Scale Development ProcedureResults (Continue) MeanVariance Std. Deviation Cronbach's Alpha AVE %KMOBartlett N of Items PA 20.1225.1375.014.659 53.637.000.863 9 PR 8.8415.9823.998.893 70.365.000.873 5 RA 6.585.6002.366.748 70.365.000.767 4 PQI 10.5217.8754.288.798 63.679.000.747 4 ASC 6.115.7652.401.652 61.077.000.585 3 SN 7.084.1192.030.673 75.356.000.500 2 Aff 12.6918.5144.303.871 72.224.000.829 4 Ava 6.745.1532.270.752 80.190.000.500 2 Acc 6.865.3402.311.811.000.500 2 BI 6.884.2202.054.653 74.269.000.500 2 Total Scale 92.43205.06214.320.796 62.563.000.914 37 Background Aim and Objectives Results Abstract