socio-economic factors affecting environmental concern and

Socio-Economic Factors Affecting Environmental Concern and Knowledge of Consumers’ Purchasing Behaviors of

Green Products: A Study of Semarang Regency Aries Susanty, Muhammad Mujiya Ulkhaq, Nia Budi Puspitasari, Heru Prastawa, Pradita

Yusi Akshinta, Pradhipta Listyawardhani Industrial Engineering Department

Diponegoro University Semarang, Indonesia

[email protected], [email protected], [email protected], [email protected], [email protected], [email protected]

Abstract

To understand the consumers’ purchasing behavior of green products, this study aims to know the different effects of socio-economic factors (gender, age, level of education, and level of income) on the environmental concern and knowledge owned by the customer through Analysis of Variance (ANOVA) statistic-test. This study used primary data that were collected through an online and offline questionnaire. In this study, 510 respondents located in the city of Semarang in Indonesia participated in the online and offline questionnaire, however, only 325 answers were valid. As a result of the ANOVA statistic-test, this study found that a significant difference among consumers of different ages, gender, and level of education in terms of environmental concern and knowledge. The customer with age group less than 30 have, female, and level of education senior high school and university have a mean value of environmental concern and knowledge higher than the other groups. On the other hand, this study fails to prove a significant difference among consumers at a different level of income in terms of environmental concern and knowledge.

Keywords ANOVA, environmental criteria, socio-economic factors, Semarang.

1. Introduction

Today, environmental protection makes the interest in the green product has grown. It’s indicated by increased manufacturers' supply (Chung and Wee, 2008) and increased consumer demand (Chen, 2008). The definition of the green product itself is not quite clear as the boundary of the concept is poorly specified and the literature still lacks a generally accepted definition (Durif et al, 2009). One definition of a green product is revealed by Albino et al (2009). A green product can be interpreted as a product that is designed to keep at minimum environmental impacts during its whole life-cycle. Typically, minimize the use of a non-renewable resource, reduce the use of toxic materials, and use the renewable resources below the usual level usage.

Then, the purchase behavior associated with green products can be interpreted as the consumption of things favorable/ valuable for the environment, recyclable, sensitive, and responsive to environmental concerns (Mostafa, 2006). According to Kim and Choi (2005), consumers with a higher environmental concern should plausibly buy green products than those who express less concern. According to Tantawi et al (2009) and Yeung (2004), environmental concern is an attitude that reflects the level of consumer apprehension of the well-being of the environment. The attitudes will be expressed in the products they purchase. Although this condition does not always happen, based on their study, Kim and Choi (2005) discovered a direct influence of environmental consideration on purchase behavior on green products. The importance of environmental concern in the variables of predicting consumers’ green consumption is emphasized by Mostafa (2009). He discovered that there was a significant difference in environmental concern between green consumers and non-green consumers. Moreover, Makatouni (2002), Padel and Foster (2005). Wang et al (2014), and Zhao et al (2014) stated that environmental concerns have a positive and direct impact on

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ecological knowledge, purchase intention, and actual purchase behavior. Then, besides environmental concern, environmental knowledge has often been assumed to be the major issues of consumer intention and actual purchase of green products (e.g., Chan and Lau, 2000; Laroche et al., 2001; Mostafa 2009; Peattie and Charls, 2011; Lee, 2011; Eze and Ndubisi 2013). Consumers’ environmental knowledge serves as the motivation to act in an environmentally friendly way (Bamberg and Moser, 2007; Moisander, 2007). Consumers who are more well-informed about issues related to the environment and the benefits of green products may have a more positive attitude toward these products (Bang, 2000).

Several justifications are specified for the variances in environmental concern and knowledge, through the context of an individual’s characteristics (e.g., gender, age, education) and contextual factors (e.g., national wealth, environmental conditions). For instance, the individual characteristics observed by Kemmelmeier et al (2002), Marquart-Pyatt and Sandra (2008), and Xiao and Dunlap (2007) have a relation to environmental concern; while Franzen and Meyer (2010), Gelissen (2007), Haller and Hadler (2008), and Marquart-Pyatt and Sandra (2012) are combining the individual and contextual characteristics. Related to an individual’s characteristics, from a long time ago, various studies have linked environmental concern and knowledge to socio-demographic factors (such as gender, age, level of education, and the level of income). However, some of the results were found to be contradictory or less consistent across surveys and samples (Dunlap and Jones, 2002). For example, several researchers (Mohai, 1992; Stern et al, 1993; Zelezny et al, 2000; Hunter et al 2004) discovered that female reveal better environmental concern than men, but others have found the opposite (Arcury et al, 1987; MacDonald and Hara, 1994; McEvoy, 1972). Then, mixed evidence for the effect of gender on environmental concern have discovered by some researchers (Blocker and Eckberg, 1997; Klineberg et al, 1998), whilst others (Arcury and Christianson, 1993; Widegren, 1988; Brown and Taylor, 2000) did not find a statistically significant effect of gender on environmental concern. Related to the level of income, D’Souza et al. (2005) found that level of income does not relate to environmental concerns on any level. Different from D’Souza et al (2005), Bennett et al. (2008) argues that there is a positive correlation between higher levels of income and education with environmental concern. In line with Benneth et al (2008), Tucker and Douglas (2006) show a positive correlation between higher levels of education and income and environmental concern. In a Howell and Laska (1992) sequential cross-sectional study related to the age hypothesis, it has been discovered that younger persons showed more concern about environmental degradation than elder persons.

Related to environmental concern, earlier studies also show an inconsistent pattern for the relationship between gender and environmental knowledge. In particular, Jain and Kaur (2006), Robelia and Murphy, (2012), Bortoleto et al (2012), Cheung et al., (2015), and Levy et al. (2016) discovered that males were more knowledgeable about environmental issues. However, Tayci and Uysal, (2012), Awan and Abbasi (2013), and Aoyagi-Usui et al. (2003), and Newman and Fernandes (2016) found that females were more knowledgeable about environmental issues than men. Then, Diamantopoulos et al., (2003) has found no significant relationship between gender and environmental knowledge. Cavalcanti Sá De Abreu and Lins (2011) found that younger consumers with high levels of education and high incomes have more knowledge and views of what is important about an environmental issue. However, Robelia and Murphy’s (2012) found that suggested that adults aged 35–65 in the U.S were more knowledgeable than younger people. Aoyagi-Usui et al (2003) also discovered that eco-awareness increased along with age, Shen and Saijo (2008) then discovered that the younger people in Shanghai was less concerned about the environment than the elder generation. The relationship between education and income levels and environmental knowledge is more consistent. Robelia and Murphy (2012) noted that undergraduate students in the U.S. tended to gain more environmental knowledge as a result of their college education. Shen and Saijo (2008) also noted that college degrees or higher in Shanghai were more environmentally concerned than those without.

1.1 Objectives

Shortly, as the environmental concern and knowledge may have a significant role as the variables for predicting customer purchase behavior of the green product and the socio-demographic factor may influence the environmental concern and knowledge differently across survey and samples, the purpose of the study is to know the different effects of socio-economic factors (gender, age, level of education, and level of income) on the environmental concern and knowledge of the customer through Analysis of Variance (ANOVA) statistic-test.



2. Literature Review

Besides Tantawi et al (2009) and Yeung (2004), the definition of environmental concern can be retrieved from Dunlap and Jones (2002), Kim and Choi (2005), and Hassan (2014). Environmental concern is related to the degree of consumers’ realization of environmental challenges and their willingness to participate personally to solve these problems (Dunlap and Jones, 2002; Kim and Choi, 2005). Hassan (2014) also defined environmental concern as the degree of consumer fear about environmental threats due to human interventions. It seems no single definition of environmental concern. Moreover, not only varied in definition, but the indicators used to measure environmental concern also varied among researchers. Stern et al (1993) revealed that environmental concern can be measured through three correlated value orientations, namely social-altruistic value (highlights concern about the prosperity of another human being), biosphere value (concern about the inhuman species or the biosphere), and egoism or self- interest orientation (best defined as ‘not in my backyard’ attitudes). More recently, according to Xiao and Dunlap (2007) and Marquart-Pyatt (2012), the environmental concern can be measured through a willingness to pay, the seriousness of different environmental problems that have been experienced within the community and on a global scale. Do Paco and Raposo (2010) only use the seriousness of different environmental problems that the respondents experience within the community and on a global scale to measure environmental concern.

Zsóka et al. (2013) described environmental knowledge as knowledge and awareness about environmental problems and feasible solutions to those problems. Other researchers use various measures to empirically assess consumers’ environmental knowledge. According to Tanner and Kast (2003), several researchers measure environmental knowledge by a look at the factual knowledge owned by the customer and the other researchers measure the environmental knowledge by a look at the impact of customer action-related knowledge. Do Paco and Raposo (2010) and Taufique et al (2016) measure environmental knowledge through the degree to which consumer is aware with present environmental issues such as ‘climate change’, ‘greenhouse gas’ etc.

3. Methods

3.1. Instruments and Measurements

This study uses a questionnaire-based survey to collect the data. The questionnaire is divided into two main sections. The first section of the questionnaire aims to collect demographic data from the respondents, such as age, gender, education, and income. The second section aims to measures the response of the respondents according to their environmental concerns and knowledge. The environmental concern (ECON) measures by 4 indicators, whereas, the environmental knowledge (EKNW) measures by 5 indicators. All the indicators are measured by using a five-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree) and all the indicators are adapted from Do Paco and Raposo (2010).

3.2 Sampling Design and Data Collection

Structured questionnaires were distributed to respondents all over Semarang, the capital of Central Java Province, Indonesia. The questionnaire was distributed directly to the respondent or using an online questionnaire on a Google form. In this case, the convenient random sampling technique was adopted for selecting the potential respondents for one month. For the offline questionnaire, the potential respondents were first approached and asked if they agreed to participate in the survey; then they were asked to fill the questionnaire on the spot or they can send back the questionnaire in one week. Then, for the online questionnaire, the link of the Google form distributed to the potential respondent by email, WhatsApp, and text messages.

3.3. Data Processing Technique

This research used factor analysis for construct validity test, Cronbach’s Alpha scores for reliability test and descriptive statistics (mean and standard deviation) to compute and assess the general pattern in the data of environmental knowledge dan concern among the participants. This research also used analysis of variance (ANOVA) to determine whether there are statistical differences in the environmental knowledge and concern between genders, age, the level of education, and income.



4. Data Collection

There were 550 questionnaires sent to the individual respondent during one month and 510 were returned, of which 325 were valid and can be used for further data processing. It is indicated an effective response rate of 92.72 percent within one month. As seen in Table 1, out of 325 respondents, the majority was female (60.98%). Most of them were 21 to 30 years old (52.35%). The majority of the respondent (52.35%) had graduated at senior high school level (57.06%) and reported had an annual income less than 1,500 USD.

Table 1. Characteristic of the respondents

No Variables Percentage 1. Gender Male 39.02%

Female 60.98% 2. Age (years old) Less than 20 22.35%

Between 21–30 52.35% Between 31–40 5.69% Between 40–50 9.41% More 50 years old 10.20%

3. Education level Elementary 0.98% Junior high school 5.69% Senior high school 57.06% University 36.27%

4. Occupation Civil servant 4.12% Employee 16.86% Entrepreneur 9.02% Others 70.00%

5. Income per annum (UD) More than 1,500 71.37% Between 1,501–2,500 10.78% Between 2,501–3,500 8.04% Between 3,501–4,500 6.08% More than 4,500 USD 3.73%

5. Results and Discussion

5.1 The Result of Construct Validity and Reliability

This research use factor analysis for construct validity test. First, the Kaiser-Meyer-Olkin (KMO) value is calculated and Bartlett’s Sphericity test is performed to check the suitability of the data for the factor analysis. The result of KMO calculation and Bartlett’s Sphericity test indicated that the data is suitable and the factor analysis can be performed on the variables as the value of KMO is 0,844 and Bartlett’s test is significant (Chi-square=1,494.612, degree of freedom=36, p<0.000). The factor analysis uses a principal component method for factor extraction and the result indicated that all indicators can be loaded into two factors. In detail, the indicator and their corresponding factors can be seen in Table 2. Moreover, to enhance the comprehension and interpretation of the result, varimax rotation with Kaiser Normalization is used during factor analysis. This research uses Cronbach’s Alpha scores to test the reliability of the scales. As seen in Table 2, all of the factors have satisfactory reliability.

Table 2. The result of factor analysis and reliability test

No Dimensions/Indicators Factor or Component Cronbach’s Alpha ECON EKNW

Environmental Concern (ECON)

1 I am very worried about the problem of pollution in common (ECON1) 0.825

0.798 2 I am very worried about the problem of depletion of ozone and the pollution of air (ECON2) 0.884



No Dimensions/Indicators Factor or Component Cronbach’s Alpha ECON EKNW

3 I become angry when I think about the damage of pollution to life (ECON3) 0.839

4 I become angry as well as frustrated when I think about the ways in which firms take the part of the pollution (ECON4) 0.541

Environmental Knowledge (EKNW)

1 I understand how to preserve and not cause loss to the environment (EKNW1)

0.657

0.845 2 I understand the meaning of global warming (EKNW2) 0.782 3 I understand the meaning of acid rain (EKNW3) 0.830 4 I understand the problem of ozone depletion (EKNW4) 0.863 5 I understand that plastic bags cause pollution and will need

many years to decompose (EKNW5)

0.582

5.2 The Result of Descriptive Statistics and Analysis of Variances

The descriptive statistics of the answer of the respondents according to their environmental knowledge (EKNW) and concern (ECON) for each age group, gender, level of education, and level of income can be seen in Table 3, Table 5, and Table 7. Then, the result of the analysis of variances can be seen in Table 4, Table 6, and Table 8.

Table 3. The descriptive statistics of the answer of the respondents for each age group

N

Mean

Std.

Deviation

Std.

Error

95% Confidence Interval for Mean

Minimum

Maximum Lower Bound Upper

Bound

ECON

< 20 years old 39 4.046 0.462 0.074 3.896 4.196 3.000 5.000 21–30 years old 178 3.874 0.504 0.038 3.800 3.949 2.400 5.000 31–40 years old 28 3.450 0.765 0.145 3.153 3.747 1.000 4.400 40–50 years old 30 3.587 0.481 0.088 3.407 3.766 2.000 4.400 > 50 years old 45 3.600 0.618 0.092 3.414 3.786 2.000 5.000

EKNW

< 20 years old 39 4.077 0.480 0.077 3.921 4.233 3.000 5.000 21–30 years old 178 4.093 0.519 0.039 4.016 4.170 2.750 5.000 31–40 years old 28 3.804 0.563 0.106 3.585 4.022 2.000 5.000 40–50 years old 30 3.858 0.453 0.083 3.689 4.028 3.000 5.000 > 50 years old 45 3.794 0.528 0.079 3.636 3.953 2.250 5.000

The result of descriptive statistics indicated that the age group less than 30 has a mean value of environmental concern higher than the other groups and the age group less than 20 years old has a mean value of environmental knowledge higher than the other groups. It seems the result supports the previous research from Howell and Laska (1992), and Cavalcanti Sá De Abreu and Lins (2011). Then, to know whether there are statistical differences in the environmental concern and knowledge between ages, the ANOVA test is performed as shown in Table 4.

Table 4. The result of analysis of variances based on age group

Sum of Squares

df

Mean Square

F

Sig.

ECON Between Groups 9.919 4 2.480 8.456 0.000 Within Groups 92.383 315 0.293

Total 102.302 319

EKNW Between Groups 5.343 4 1.336 5.053 0,001 Within Groups 83.281 315 0.264

Total 88.624 319

A significant difference among consumers at different ages in terms of environmental concern and knowledge shown in Table 4. To find out which age groups are different, a Tukey post-hoc test is performed. The result of the Tukey



shows that environmental concern of less than 20 age group is not statistically different with the other age groups, however, the environmental concern of 21-30 age group is statistically different from 31-40 age group (dif means 0.289; p-value 0.047) and 50 and above age group (dif. means 0.298 p-values 0.005). The results of the Tukey also show that environmental knowledge of less than 20 age group is statistically different from 31-40 age group (dif. means 0.596; p-value 0,000), 41-50 age group (dif. Means 0.459; p-value 0.005), and 50 and above age group (dif. means 0.446; p-value 0.002). Then, the 21-30 age group is statistically different from 21-30 age group (dif means 0.424; p-value 0.001) and 50 and above age group (dif. means 0.274; p-value 0.022). The differences between age groups can be seen more clearly from the following figure (see figure 1).

1= < 20 years old 2= 21–30 years old 3= 31–40 years old 4=40–50 years old 5= > 50 years old

Figure 1. The differences between age group for environmental concern and knowledge

Table 5. The descriptive statistics of the answer of the respondents for each gender group

N

Mean

Std. Deviation

Std. Error


Minimum

Maximum Lower Bound

Upper Bound

ECON Male 130 3.929 0.523 0.046 3.838 4.020 2.000 5.000 Female 195 4.053 0.525 0.038 3.978 4.127 2.250 5.000

EKNW Male 130 3.777 0.508 0.045 3.689 3.865 2.000 5.000 Female 195 3.807 0.600 0.043 3.722 3.892 1.000 5.000

The result of descriptive statistics indicated that female have a mean value higher than a man in their environmental concern and knowledge. It seems, the result supports the previous research from Aoyagi-Usui et al. (2003), Hunter et al 2004), Tayci and Uysal (2012), Awan and Abbasi (2013), and Newman and Fernandez (2016). Then, to know whether there are statistical differences in the environmental concern and knowledge between genders, the ANOVA test is performed as shown in Table 6.

Table 6. The result of analysis of variances based on gender

Sum of

Squares

df Mean Square

F

Sig.


Total 89.997 324

EKNW Between Groups 0.071 1 0.071 0.223 0.637 Within Groups 103.201 323 0.320

Total 103.272 324

There is a significant difference among consumers of different gender in terms of environmental concern shown in Table 6; however, there are no significant differences in terms of environmental knowledge between males and

4.2000 4.0000 3.8000 3.6000 3.4000

0 1 2 3 4 5 6

ECON EKNW



females. Graphically, the differences between gender in terms of environmental concern and knowledge can be seen more clearly in the following figure (see figure 2).

1= Male 2= Female

Figure 2. The differences between gender for environmental concern and knowledge

Table 7. The descriptive statistics of the answer of the respondents for each level of education group

N

Mean

Std. Deviation

Std. Error


Minimum

Maximum Lower Bound

Upper Bound

ECON Elementary and junior high school

27

3.7037

0.542

0.104

3.489

3.918

2.250

4.500

Senior high school 173 4.0434 0.518 0.039 3.966 4.121 2.250 5.000

University 125 4.0120 0.520 0.046 3.920 4.104 2.000 5.000 EKNW Elementary and

junior high school

27

3.4741

0.870

0.167

3.130

3.818

2.000

5.000

Senior high school 173 3.7827 0.520 0.040 3.705 3.861 1.000 5.000

University 125 3.8816 0.519 0.046 3.790 3.973 2.600 5.000

The result of descriptive statistics indicated that customers with the level of education senior high school and university have better or higher mean value on environmental concern and knowledge than elementary and junior high school. It seems, the result supports the previous research from Tucker and Douglas (2006) and Shen and Saijo (2008). Then, to know whether there are statistical differences in the environmental concern and knowledge between the levels of education, the ANOVA test is performed as shown in Table 8.

Table 8. The result of analysis of variances based on level of education

Sum of Squares

df

Mean Square

F

Sig.

ECON Between Groups 2.710 2.000 1.355 4.999 0.007 Within Groups 87.286 322.000 0.271

Total 89.997 324.000

EKNW Between Groups 3.745 2.000 1.872 6.057 0.003 Within Groups 99.528 322.000 0.309

Total 103.272 324.000

4.1000 4.0500 4.0000 3.9500 3.9000 3.8500 3.8000 3.7500

0 1 2 3

EKNW ECON



As it is seen from Table 8, there is a significant difference among consumers at a different level of education in terms of environmental concern and knowledge. To find out which age groups are different, a Tukey post-hoc test is performed. The results of the Tukey shows that environmental concern of elementary and junior high school group is statistically different from senior high school group (dif. means -0.339 p-value 0.05) and university group (dif. means -0.308 p-value 0.15); whereas the environmental concern of senior high school is not statistically different with university group (0.0314 p-values 0.865). In line with environmental concern, environmental knowledge of elementary and junior high school group is statistically different with a senior high school group (dif. means -0.309 p-value 0.021) and university group (dif. means -0.408 p-value 0.002); whereas, environmental knowledge of senior high school group is not statistically different with university group (diff. means -0.099 p-value 0.285). Graphically, more clearly, the differences between the level of education group can be seen from the following figure (see figure 3).

1=elementary and junior high school 2= senior high school 4= university

Figure 3. The differences between the level of education for environmental concern and knowledge

Table 9. The descriptive statistics of the answer of the respondents for each level of income group

N

Mean

Std. Deviation

Std. Error


Minimum

Maximum Lower Bound

Upper Bound

ECON < 1,500 USD 234 3.813 0.582 0.038 3.738 3.888 1.000 5.000 1,501–2,500 USD 80 3.748 0.535 0.060 3.628 3.867 2.600 5.000 2,501–3,500 USD 9 3.889 0.267 0.089 3.684 4.094 3.400 4.200 > 3,501 USD 2 3.200 0.283 0.200 0.659 5.741 3.000 3.400

EKNW < 1,500 USD 234 4.018 0.561 0.037 3.946 4.090 2.000 5.000 1,501–2,500 USD 80 3.994 0.428 0.048 3.898 4.089 3.000 5.000 2,501–3,500 USD 9 3.861 0.309 0.103 3.624 4.099 3.250 4.250 > 3,501 USD 2 3.250 0.354 0.250 0.073 6.427 3.000 3.500

The result of descriptive statistics indicated that customers with a higher level of income have lower environmental concerns and knowledge compared to those who have a higher level of income. It seems the result of data processing does not support the previous research from Tucker and Douglas (2006) and Bennett et al. (2008). Then, to know whether there are statistical differences in the environmental concern and knowledge between the levels of income, the ANOVA test is performed as shown in Table 10. The result of the ANOVA test indicated that the level of income does not have associated with environmental concerns on any level (F= 1,661; p-value 0.175). The result of the ANOVA test also indicated that level of income do not have associated with environmental knowledge on any level (F= 1.091); p-value 0.353).

4.1000

4.0000

3.9000

3.8000

3.7000

3.6000

3.5000

3.4000 0 1 2 3 4

ENVKNW ENVCON



Table 10. The result of analysis of variances based on level of income

Sum of Squares

df

Mean Square

F

Sig.


Total 89.997 324

EKNW Between Groups 1.042 3 0.347 1.091 0.353 Within Groups 102.230 321 0.318

Total 103.272 324

6. Conclusion

The purpose of the study is to know the different effects of socio-economic factors (gender, age, level of education, and level of income) on the environmental concern and knowledge of the customer through the Analysis of Variance (ANOVA) statistic-test. As a result of the ANOVA statistic-test, this study found that a significant difference among consumers of different ages, gender, and level of education in terms of environmental concern and knowledge. The customer with age group less than 30 have, female, and level of education senior high school and university have a mean value of environmental concern and knowledge higher than the other groups. So, the result of this research supports the previous study on gender differences in environmental concern and knowledge. Typically, female tending to show higher levels of concern and knowledge relative to men. Age was found to be contrary related to environmental concern and knowledge, older tend to be less concerned about the environment than younger cohorts. Also, the education level was found to affect the environmental concern and knowledge of the Semarang public. People with higher levels of education tended to be more likely to engage in environmental concern and knowledge.

This study contributes both to theory and practice. Theoretically, this study contributes to the fields of consumer behavior. The research has helped us to better understand how socio-demographic variables shape environmental concern and knowledge in the Semarang public. Furthermore, the results can be utilized as a reference to track public trends on environmental concerns and knowledge issues in the future. Practically, the results of this study give some recommendations for the business. For business, the promotional messages for a specific gender can be effectively applied by marketers as gender divergence was found to occur in environmental concerns and knowledge of consumers. Another essential insight delivered by current research is, to effectively use the environmental concern and knowledge from their customers, the marketers need to craft strategies regard to specific demographic targets. Such targeting can also be effective as female, young consumers, and high level of education are more readily influenced by marketer generated information than male, older consumers, and lower level of education.

This study was limited to only consumers in Semarang and did not cover all regions in Central Java Province as well as in Indonesia and the pro-environmental variables used are limited to environmental concern and knowledge. Therefore, it is recommended to do more research on a greater scale with more (or various) criteria. A wider geographical area could be considered, including a nation-wide study. The more pro-environmental variable could be considered, such as environmentally friendly buying behavior, environmental activism, recycling, perceived consumer effectiveness, resource-saving, economic factor, and skepticism towards the environmental claim.

Acknowledgment The authors wish to acknowledge to the Rector of and Head of Institute for Research and Community Service Diponegoro University for allowing the authors to conduct this research through the “Riset Publikasi International” the budget year 2020

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Biographies Aries Susanty is a Professor in the field of Industrial Engineering and also a lecturer at the Department of Industrial Engineering, Diponegoro University, Semarang, Indonesia. She obtained her Doctoral in Industrial Engineering from the Bandung Institute of Technology. She served as Secretary of Master Program of Industrial Engineering and Management from 2017. Through his 20+ years of experience in teaching and research at the Diponegoro University, she has established an overarching research area in supply chain modeling, supply chain governance, supply chain policy, procurement and logistics strategy, and organization behavior. Her research track record has been demonstrated by winning many research grants from the Indonesian government and Diponegoro University. She has published more than 50 technical papers in journals and conferences. She also coordinated multiple academic and industrial research projects. She has completed the supervision of 5 Master Student and over 60 Undergraduate Students. Muhammad Mujiya Ulkhaq is a Researcher in the Department of Industrial Engineering at Diponegoro University, Indonesia. He obtained his bachelor’s degree in Industrial Engineering at Diponegoro University, Indonesia, and master’s degree in Engineering Management at Jönköping University, Sweden. He is now a Ph.D. student in Analytics for Economics and Management at the University of Brescia, Italy. His research interests include efficiency & productivity measurement, service & quality management, campus sustainability, and mathematical & statistical modelling in management, economics, and the environment. Mr. Ulkhaq's works have been published in several reputable journals and presented in more than 50 international conferences. He also serves as a reviewer in some journals and international conferences. Nia Budi Puspitasari is a Lecturer in the Department of Industrial Engineering, Diponegoro University. She obtained her Master's Degree in Industrial Engineering from the Bandung Institute of Technology. Her research interests include management, organization, and sustainable consumption, Heru Prastawa is an Associate Professor, a member of Work System Engineering and Ergonomic Laboratory, in Industrial Engineering, Diponegoro University. He obtained his Doctoral in Industrial Engineering from Sepuluh Nopember Institute (ITS) Surabaya, Masters in Technology Assessment from Universite Marseille III, Marseille, France. His research interests include Human Factors, Ergonomics, User Experience, and Manufacturing Systems. He is a member of IAE. Pradita Yusi Akshinta is a graduate of the Department of Industrial Engineering, Diponegoro University. Her research interests include management, organization, and sustainable consumption. Pradhipta Listyawardhani is a graduate of the Department of Industrial Engineering, Diponegoro University. Her research interests include management, organization, and sustainable consumption.



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