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China’s Triple Bottom line (TBL) Challenge: Exploring How Demographics and Values Shape Preferences of Future Managers and Engineers toward Profit, People and Planet


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2018 International Conference on Physics, Computing and Mathematical Modeling (PCMM 2018) ISBN: 978-1-60595-549-0

China’s Triple Bottom-line (TBL) Challenge: Exploring How

Demographics and Values Shape Preferences of Future

Managers and Engineers toward Profit, People and Planet



, Waseem A KHAN


, Chui S HOH


and Hui LI



School of Management, Xiamen University, China


Institute for Financial and Accounting Studies, Xiamen University, China

3Institute of Education, Xiamen University, China

*Corresponding author

Keywords: Triple Bottom-line, Environmental Values, People-oriented Values, Materialism, China.

Abstract. More recently, scandals of corporate malpractices, human rights exploitation and use of high-impact materials, ecological degradation are now becoming serious threats to China’s TBL initiatives for sustainable economic growth. Some argue that such disruptions are linked to changing demographics and altering value systems in Chinese society. Despite practical and theoretical significance, current literature offers no empirical study that examines potential micro-antecedents to TBL preferences of Chinese professionals, especially those in working in the domain of natural sciences. Responding to such knowledge gaps, the current study analysed data from self-reports of 383 business and engineering students. Results indicated that demographic factors effects materialism, which in turn, generates favourable attitude towards TBL (profit), but negatively relates to socio-environmental values and TBL (people and planet). Practical implications are discussed for policy makers, educators and business leaders.


While rapidly transitioning into a consumer-based economy, a number of unaddressed issues overshadow China’s socio-economic prosperity. According to experts, growing materialism, narcissism, low people-orientation, escalating environmental degradation and CO2 emissions are some of the challenges that China must recognize and rectify in time before it is too late. Beyond addressing social turpitude, there is consensus among scholars that sustainable and eco-friendly economic growth rests on effective implementation of TBL [1]. As a business concept, John Elkington first introduced TBL in 1997 that requires firms to design products and operate to benefit profit (organization), people (society) and planet (environment). Given that corporate social responsibility (CSR) suffers from vagueness and lack of precise framework, academics and organizations are incorporating TBL as a proximal performance metrics to address socio-ecological issues [2]. An academic inquiry on CSR also endorses TBL as a more precise measure compared to generic CSR approaches for examining sustainable economic success [3]. Though businesses are now forming local and global partnerships to effectively address TBL, such initiatives remain nascent in developing economies e.g., China [4]–[6]. Despite asserted role of young professionals and students in TBL, empirical studies on micro-level factors that shape TBL attitudes of young professionals are virtually absent, especially those including views of natural sciences professionals [1], [7].

Of possible explanations, some authors implicitly point out that transforming demographics

triggered by macro-micro factors (e.g., Chinese economic reforms, little emperors syndrome)[8] [9]


potential antecedents to immoral values and business ethics [17] [18] [19]. Despite that, the complex interaction between demographics, values, and specifically TBL has not been examined to this date. This paper builds on earlier works, in particular that of Piper et al. [20] and Meng et al. [21], to address the knowledge gap in Asian environmental research by examining relationships of selected demographic factors, student values (e.g., materialism) and TBL preferences in the context of China. If social, economic and environmental sustainability of businesses in China is contingent on successful integration of TBL into organizational norms and operational codes [1], [5], [6], [20], then

examining etiology of TBL proves to be logical and theoretically significant [20], [21].

The structure of this paper is as follows. First, we develop the hypotheses based on review of empirical and theoretical studies on the topic. Next, we discuss method that includes participants, procedures, measures and statistical analyses. After that, we present the findings and results, followed by discussion, conclusion and implications.

Literature Review

Previously, a number of scholars in different countries such as, India, Canada, Finland and USA (Arlow [17]; Aspen Institute [22]; Wong et al. [23]; Lamsa et al. [24]) have studied attitudes and behaviors of business students towards CSR, however, the authors could locate only two studies, as of this writing, on student perception of TBL, both conducted by Piper and her colleagues at a Canadian university [20], [21]. Consistent with findings of Lamsa et al. [24], Borkowski and Ugras [18] and Keith et al. [25], Piper et al. [20] found that female students show stronger preference for ethical business conduct (TBL: planet and people) than male students, but Yamamura and Stedham [26] and some others researchers find such differences to be insignificant, coincidental or context-driven [27], [28]. Additionally, studies on the effects of age and business education as predictors of negative attitude toward CSR reflect mixed findings. Despite support, some authors contend that ethical attitudes of male and female students tend to converge positively with age and work experience [29], [30].


Hypothesis Development

Demographics Factors and Materialism

Drawing from earlier value surveys (e.g., Rokeach [41] and Schwartz [40]), a number of definitions of materialism have been offered to this date. Richins and Dawson [42] define materialism as expression of desire for material things and importance of these things for one’s welfare, happiness and satisfaction. Belk [8], however, identifies three defining aspects of materialism including one’s cognitive disposition to view, acquire and place material possessions as symbol of success and happiness and satisfaction.

From a theoretical perspective, a number of surveys endorse that demographic factors play a critical role in determining student’s values e.g., materialism, ethics, and environmental beliefs. Despite that, these studies offer mixed and inconclusive views on the effects of age, education-level, income, gender and religion on values and ethical behaviors. For instance, some authors identify marginal or insignificant effects of age on materialism [35], [43], while other findings offer significant variation among age-groups i.e. middle-age group and young students are found to elicit more materialism than children and older groups [44]. More recently, Parashar and Jain [35] found that young and middle-aged show strong signs of materialism, a view consistent with other recent Chinese surveys

[45], [36]. Furthermore, although some scholars argue that high-income groups display high

materialism [16], [43], meta-analytical reviews suggest that students from lower-income groups/economically deprived backgrounds display high materialism in China [34], [46]. In another meta-analytical review of 47 studies, Borkowski and Ugras [18] offer empirical and theoretical support for low materialism among female than male students, a view consistent with recent studies [24], [25].

In contrast, some academics consider that such female dominance could be merely coincidental, scenario-driven or due to social desirability response biases [27]. Payan and Iyer [28] empirically established that female bias is merely context-driven or scenario-based, as similar educational environment often moderate such differences. Such a concept makes sense considering that some media reports and articles identify females as more materialist than their male Chinese professionals, even labeling them as hyper-materialist [47][48]. In the same way, prior work indicates that business students assign greater importance to instrumental possessions, money, material success that often increase with each year of educational experience. Bergman et al. [49] found that student enrolled in business-related major show higher materialism and narcissism than students from non-business study majors, a view consistent with other studies [20], [21]. Robak et al.’s [50] also offer (and found support for) business education as a proximal predictors of desire for money-making, profit and self-enchantment. Of few studies on religiosity and materialism, Siu et al. [33] found that religion positively affect ethical values and behaviors among Chinese students. Consistent with Ramasamy et al.’s [32], authors including Conroy et al. [51] contend that factors beyond education experience and business major such as, implicit and explicit religion negatively affect pursuit of money, materialism or financial self-interests, while inducing positive attitudes. Based on above, it is predicted that demographic factors may affect materialistic values in their own distinct way, as formulated below;

H1. Materialism will increase with age.

H2. Materialism will increase with family income.

H3. Materialism will be higher among Chinese female than male students.

H4. Materialism will positively relate to business study major than engineering majors. H5. Materialism will increase with years of education.

H6. Materialism will be higher among students with no religion than those with religion.

Materialism, Ethical Values and TBL Preferences


choices [34], [52], which cues their strong preference for TBL (profit) to the detriment of social and environmental issues i.e. TBL (people and planet). Huang et al. [53] found that materialistic individuals in China display strong tendencies to actively benefit from illegal, unethical and questionable business and social activities, while considering such passive benefit as legitimate. Furthermore, the well-documented evidence on the negative effects of materialism on environmental ethics clearly delineates its potential repercussions for environmental values, as well as attitude toward TBL (planet). Witt and Stahl’s [54] cross-national study also found that stakeholder salience or values (e.g., people and environment) often lies at the bottom of priority list in China, as managers single-mindedly pursue economic values above all functions. Kolodinsky et al. [31] also found support for materialism as a leading cause that exerts negative impact on students’ business ethics preference with respect to society and environment e.g., community participation and green/eco-friendly manufacturing. As a recent intervening concept, a number of studies suggest that economic values (profit-seeking), instilled through exposure to business education, elicit negative attitudes, behaviors and end states towards stakeholder-centered initiatives [54], [55]. As Chinese students, espousing materialistic values, are more likely to forgo even deeply-rooted intrinsic values for money, negative attitudes towards TBL aspects (e.g., people and planet) are inevitable. Such reasoning depicts implicit beliefs stated in a series of studies conducted by Westerman and their colleagues [37]–[39]. Implicitly or explicitly, these authors suggest that narcissism and materialism among students not only undermine ethical values but also induce negative attitudes and behaviors toward an array of corporate undertakings e.g. TBL, eco-investment, green production etc. In line with such theoretical and empirical underpinning, it is speculated that;

H7. Materialism will positively relate to preference for TBL (profit).


H8. Materialism will negatively relate to people-oriented values and TBL (people). H9. Materialism will negatively relate to environmental values and TBL (planet).

Figure 1. Conceptual framework for relationships of demographics, values and triple bottom-line.


Participants and Procedures

Participants were provided by a popular training institute with campuses all over China who facilitated the data collection process and survey administration, in collaboration with researchers. Using systematic sampling, 450 potential respondents were extracted from the total list for data collection. A total of 383 students from different Chinese universities responded to the survey (response rate = 88%). The institute’s officials sent an email to respondents with informed consent forms, study purpose, research ethics content and a return address. Despite its apparent advantages, the authors were given limited access to data due to legal restrictions and privacy issues. The survey

Materialist Values Profit (Organization) Age

Gender Family Income

Education Level

People (Community)

Planet (Environment)

Religion Study Major

H3 H4 H5 H6

Environmental Values H8

H9 H1

Demographics Values TBL Dimensions



was first developed in English and then translated into Chinese using Brislin back-translation

approach [56]. The authors also employed two independent language experts to improve the consistency of questionnaire who were kept blind to study’s objectives. For analyses of data, IBM’s SPSS 21 was used for testing relationship using different methods such as, reliability, validity,

regression, correlations, two-sample t-test, and ANOVA. Of some disclosed demographics, the data

is as follows: gender (male, 161, 42%, female, 222, 58%); education years (1st yr. = 150, 2nd yrs. = 24,

3rd yr. = 104, 4th yr. = 5, master 1st yr. = 98); age group (min. = 179, max = 199, max = 5); religion

(with religion = 131, without religion = 252); study major (business = 187, engineering = 196).


Values Survey. Richins and Dawson [42] 6-items battery was adopted to measure materialist

values (MV), corresponding to TBL (profit) with 3 dimensions: centrality (individuals’ possessions

hold a pivotal role in one’s life); happiness (individual well-being and satisfaction relies on the extent

of possessions); and success (the degree of one’s belief that success in life is defined by the extent of

possessions they have). Cronbach’s alpha value of 0.72 suggested that the scale items demonstrated sufficient reliability. Sample items include: “It is really true that money can buy happiness”, and “I

would be happier if I could afford to buy more things”. With reliability scores averaging 0.85,Haws et

al. [57] 6-item scale was used to measure environmental values that corresponds to TBL (Planet). Sample items include “I consider the potential environmental impact of my actions when making decisions,” and “I would describe myself as environmentally responsible” Webb et al. [58] 5-items scale was used to measure people-oriented values (PV). With an average alpha value of 0.81, the scale showed consistent reliability. Some sample items include, “I believe that a person should be more helpful towards other in society,” and “I prefer donating to charities that address social concerns” (e.g., hunger, environmental awareness, poverty).

TBL (profit, people and planet). Piper et al. [20] 15-items scale was used to measure TBL including three dimensions namely profit, people and planet (Environment). Students were asked to report their attitude towards social well-being, profit-maximization and environmental concern. Respondents were asked questions on three aspects including importance of TBL knowledge, definition of a well-run company, and managerial responsibilities. Sample items include: do you agree that, we should; “Possess the knowledge to maximize profits and provide a return to business owners,” Possess the knowledge to preserve natural resources and must know about the actions that will not harm the natural environment.”

Results and Findings

Descriptive Statistics

Table 1 below exhibits the descriptive statistics including mean, standard deviation, and correlations. This correlation matrix suggests that: demographic variables positively correlate with materialism (MV), except for the study major, while the same insignificantly associate with MV, environmental values (EV), people-oriented values (PV) and TBL; MV negatively correlate with EV, PV, TBL (planet and people), but positively correlated with TBL (profit); religion negatively correlates with PV, TBL (planet), and education-level negatively correlate with PV, TBL (planet and people); EV positively correlates with PV, TBL (planet and people), and; PV positively correlates with TBL (planet), and TBL (planet) positively correlated with TBL (people). The correlation matrix offered significant empirical support to proceed with hypotheses testing.

Regression Analyses

Table 2 presents the results of two-step multiple regression analysis, as suggested in earlier studies [59]. After testing effects of demographic variables as independent variables on dependent variables


indicated insignificant multi-collinearity contamination. From the results of M1, we found that hypotheses related to family income (H2), gender (H3), educational-level (H5) and religions (H6) were accepted: females were found to be more materialist than male students; materialism increased with income and education-levels [13]; students with religion display low materialism than those without religion i.e. -0.286 (p < .01). The acceptance of H5 indirectly supported assumptions concerning age as antecedent to MV (H1). For the effects of materialism on values and TBL aspects the results showed that H7 was accepted as materialism elicit profit-orientation, indicated by differences between M10 - M11 (0.139, p < .01). For people-oriented values and TBL (people), the value of difference between M2 and M3 suggested that materialism inversely relate to people-oriented values (-0.360, p < .01) and TBL (people) (-.164, p < .01). Although relatively weak and almost insignificant, the value of difference between models (M4-M5; M6-M7) showed a negative relationship of materialism with EV and TBL (planet), thereby rejecting H9.

Table 1. Mean, Standard Deviation and Correlations.

Study Variables 1 2 3 4 5 6 7 8 9 10 11

1 Gender 1

2 Religion -.020 1

3 Family Income .051 .092 1

4 Study Major .004 .035 .019 1

5 Education Level .022 -.055 -.112* -.062 1

6 MV .175** .254** .284** .004 .104* 1

7 EV .013 -.063 -.059 .022 -.072 -.286** 1

8 PV .002 -.127* -.060 .025 .194** -.152** .231** 1

9 TBL (Planet) .042 -.108* .009 -.022 -.165** -.110* .306** .425** 1

10TBL (People) .031 -.081 -.124* -.076 -.111* -.202** .160** .070 .170** 1

11TBL (Profit) .039 .050 -.023 -.011 -.058 .159** -.067 .069 .043 -.050 1

Mean .58 .291 2.59 1.56 .272 3.653 3.543 3.573 3.964 3.791 4.059

S.D. .494 .455 1.283 .497 .448 .699 .849 .718 .726 .717 .488

Notes: n = 383; ** p < .01; * p < .05. TBL = Triple bottom-line, MV = Materialistic values, PV = People-oriented values. Table 2. Coefficients (t-values) estimated in the linear regression model.


Variables Models

Independent Variables Values

Intercept Gender Religion Family Income


-level MV R

2 ∆R2 F ∆F

MV M1 3.080** 0.239** -0.286** 0.139** 0.058* 0.158 17.602

PV M2 3.685** 0.011 0.160 -0.033 -0.043 0.017 0.017 1.635 1.63

M3 4.792** 0.097 0.057 0.016 -0.022 -0.360** 0.091 0.074 7.552** 30.70**

EV M4 3.829** 0.000 0.224 -0.030 -0.091 0.064 0.064 6.408** 6.41**

M5 4.148** 0.025 0.194* -0.016 -0.085** -0.104† 0.072 0.009 5.854** 3.47† TBL (Planet) M6 4.302** 0.052 0.251** 0.012 -0.076** 0.053 0.053 5.233** 5.23**

M7 4.303** 0.074 0.226** 0.024 -0.071** -0.088 0.059 0.006 4.683** 2.40 TBL (People) M8 4.027** 0.045 0.199* -0.064* -0.057* 0.048 0.048 4.765** 4.76**

M9 4.531** 0.084 0.152 † -0.042 -0.048* -0.164** 0.070 0.021 5.613** 8.62** TBL (Profit) M10 4.115** 0.035 0.010 -0.012 -0.019 0.006 0.006 0.555 0.55

M11 3.688** 0.002 0.050 -0.031 -0.027† 0.139** 0.039 0.033 3.058* 13.00** Notes: n = 383. **p < .01; *p < .05; † p < .10. EV= Environmental values, PV = People-oriented Values, MV = Materialist

values, TBL = Triple bottom-line.

Independent Two-Sample t-Test

Below, Table 3 presents the results of independent two-sample t-test by groups and levels. The results


year of education (1st yr. - final yr. = 3.520 - 4.467), as well as family income (lowest to highest: 3.379 - 3.974), confirming that each passing year adds to materialism and negatively influence pro-social

attitudes and behaviors (H5) [21], [60]–[62]. For corroboration, the two-sample t-test was conducted


to assess the links between demographics, materialism, environmental and people-centered values and TBL. The t-value of difference between male and female (-3.471, p value = 0.001) and religion (3.721, p-value = 0.000 < 0.005) supported prior assertions that religion and gender are proximal predictors of materialism and ethical attitudes among students.

Table 3. Descriptive Statistics Means and S.D.

Demographics Groups and Levels MV EV PV Planet People Profit

Gender Male 3.509

(0.726) 3.030 (0.913) 3.571 (0.802) 2.929 (0.730) 3.766 (0.681) 4.037 (0.494)

Female 3.757

(0.661) 3.052 (0.802) 3.574 (0.652) 2.990 (0.724) 3.810 (0.742) 4.075 (0.484)

Religion With 3.404

(0.922) 3.172 (0.932) 3.737 (0.702) 3.132 (0.609) 3.955 (0.753) 4.072 (0.417)

Without 3.753

(0.555) 2.985 (0.807) 3.504 (0.715) 2.893 (0.760) 3.723 (0.692) 4.052 (0.514)

Study Major Business 3.650

(0.717) 3.022 (0.841) 3.552 (0.770) 2.982 (0.728) 3.853 (0.664) 4.065 (0.502)

Engineering 3.655

(0.686) 3.060 (0.857) 3.589 (0.676) 2.950 (0.726) 3.744 (0.753) 4.055 (0.478) Family Income

<25000 3.379

(0.802) 3.174 (0.937) 3.693 (0.712) 3.028 (0.736) 3.944 (0.702) 4.148 (0.465)

25001 - 40000 3.548

(0.683) 2.949 (0.833) 3.482 (0.809) 2.819 (0.737) 3.769 (0.721) 3.958 (0.546)

40001 - 100000 3.809

(0.523) 2.977 (0.796) 3.556 (0.647) 2.969 (0.656) 3.751 (0.649) 4.003 (0.444)

100001 - 200000 3.821

(0.615) 3.138 (0.793) 3.533 (0.735) 3.046 (0.807) 3.705 (0.799) 4.134 (0.516)

>200000 3.974

(0.689) 2.856 (0.833) 3.556 (0.640) 2.942 (0.670) 3.666 (0.725) 4.047 (0.414) Education Level

Undergraduate 1st yr. 3.520 (0.756) 3.119 (0.842) 3.743 (0.555) 3.117 (0.605) 3.807 (0.723) 4.015 (0.474) Undergraduate 2nd yr. 3.799

(0.631) 3.225 (0.930) 3.567 (0.777) 3.017 (0.618) 3.936 (0.624) 4.354 (0.526) Undergraduate 3rd yr. 4.467

(0.398) 3.100 (1.435) 4.000 (0.825) 3.360 (0.434) 4.067 (0.494) 4.300 (0.326)

Master 1st yr. 3.672

(0.665) 2.972 (0.686) 3.378 (0.781) 2.804 (0.774) 3.628 (0.720) 3.939 (0.471) Notes: n = 383.

Table 4. T-values (Sig.) in independent two-Sample t – test.

Demographics Groups MV EV PV Planet People Profit

Gender Male -3.471 -0.245 -0.032 -0.814 -0.598 -0.755

Female (0.001) (0.807) (0.975) (0.416) (0.550) (0.450)

Religion With 3.721 -1.960 -2.905 -2.947 -2.903 -0.405

Without (0.000) (0.051) (0.004) (0.003) (0.004) (0.686)

Study major Business 0.073 0.431 0.485 -0.430 -1.480 -0.215

Engineering (0.942) (0.667) (0.628) (0.667) (0.140) (0.830) Notes: n = 383. EV= Environmental Values, PV = People-oriented Values, TBL = Triple bottom-line


as seen in Table 5, non-materialists students scored high on socio-enviromental values and TBL (planet, people) than materialists (sig. levels = .000, .003, .029, .000 and .001, respectively), which cue that materialism is an antecedent to values and TBL. In addittion, the t-test of differences (.674, .387, -.243, 0.433 and -0.24) show that materialist depict less environmental and people-centered values, as well as TBL (planet and people) preferences.

Table 5. T-test for Difference (Materialist vs. Non-materialist).

Study Variables Materialism Non-materialism Difference Sig.

EV 3.428 4.101 0.674 0.000

PV 3.497 3.884 0.387 0.003

TBL (Planet) 3.917 4.160 0.243 0.029

TBL (People) 3.723 4.157 0.433 0.000

TBL (Profit) 4.108 3.860 -0.248 0.001

Notes: n = 383. EV= Environmental Values, PV = People-oriented Values, TBL = Triple bottom-line

Analyses of Variance (ANOVA)

As seen in Table 6, the ANOVA test was conducted to determine the nature of interactions between demographics (family income and education) and materialism. Given the p-value of ANOVA (0.000 <0.05), the extent of materialism significantly differed across levels of education and family income groups in LSD-multiple comparison, represented by L1, L2, L3, L4 and L5. From the p-value of the differences, it can be observed that family income levels from 1-2 (< ¥25000 - ¥40,000) and 3-5 (¥40001- > ¥200,000) depict distinct patterns, where former showed a sharp increase in materialism, and the later demonstrated a slow and steady rise. Additionally, the p-value of ANOVA (0.004 < 0.05) indicated significant effects of education years on materialism, supporting H5. From these

differences, it was quite interesting to note that 2nd year students demonstrated less materialism

compared to other groups including 1st, 3rd and masters.

Table 6. Significance of LSD- Multiple Comparison of materialism (by family income and years of education).

Levels L1 L2 L3 L4 L5

Family income

L1: < ¥25,000 - - - - -

L2: ¥25,001 - ¥40,000 0.0875 - - - -

L3: ¥40,001- ¥100,000 0 0.0099 - - -

L4: ¥100,001 - ¥200,000 0 0.0129 0.9081 - -

L5: >200000


L1: Undergraduate 1st year - - - - -

L2: Undergraduate 2nd year 0.0669 - - - -

L3: Undergraduate 3rd year 0.0093 0.7558 - - -

L4: Undergraduate 4th year 0.0027 0.0495 0.0238 - -

L5: Master 1st year 0.0911 0.4199 0.4209 0.0124 -

Notes: n = 383



low-income group members than those in the middle or upper-income groups. With economic stability, middle and upper income group members tend to align with global ethical values due to reason such as, face-saving, ethical awareness, etc [45], [63]. Furthermore, religion showed positive association with pro-social and environmental values, people and planet aspects of TBL, and negative link with materialism and TBL (profit), which mirrors prior findings that religion mitigates immoral attitudes and behaviors [32], [33]. Of significance, the analyses of materialism (by education-level) highlighted that materialism took a dip in the second year but regained pace in the subsequent years. A possible reasoning could be the presence of social desirability, peer pressure or positive educational experience [25], [28], but perceived economic or social pressures tend to undermine such positive effects when students wake up to harsh realities of real world in the following years.

Similarly, the presence of strong materialism among females echoes prior beliefs that female and male differences are either due to context and scenario or merely coincidental [25], [28]. Possibly, high materialism among Chinese female students (in a masculine and rapidly evolving society like China) depicts a paced quest for securing social and economic recognition during prime years of youth. In addition, the indifferences of materialism among business and engineering major students point to shared drive for money and success that accumulates overtime since early childhood, a view that mirrors earlier studies [36]. Although initial analyses could not strongly validate decisive link of materialism with either environmental values or TBL (planet), the inter-group comparisons (materialist vs. non-materialist) offer support to present beliefs that such reasoning might be true. In line with previous work, business and engineering students (as future professionals) bearing materialistic values are more likely to undermine needs of people and environment, while engaging in profit-seeking at the expense of energy, environment and community [20], [21], [49].

Organizational Implications

The study’s findings offer a number of important implications for policy makers, academics and commercial organizations in China. The following section presents potential repercussions of current findings for key stakeholders.

Policy makers: Government

These findings assert the need for policy makers in the government to work with educational and commercial organizations to develop understanding of antecedents that cause socio-environmental disruption in China. Indeed, Chinese Communist Party has recently taken some steps to promote integration of moral content from folk religions (e.g., Taoism, Confucianism, Buddhism, and others) in teaching, training and development programs, but there is a long way to go. The observed relationship of materialism with low income and education cue alarming signs of perceived income inequality and disruptive educational experience, respectively [52]. Thus, decision-makers need to reassess national action plans to address macro-micro factors that are negatively altering values of emerging professionals, who in the near future, would take charge of commercial, technical and industrial operations. They must also recognize that they face serious developmental challenges that underlie unique demographic factors coupled with nascent awareness of operational norms concerning TBL [1], [64]. Instead of just articulating policies and regulations, they must take a step further to improvise a “transnational TBL approach” (rather than local or global approach) for translating TBL into actual policies, procedures and practices of social and commercial institutions in

China [54]. Mirroring the 17 United Nation’s Sustainable Development Goals (SDGs) or

Agenda 2030”, the current findings assert the need for policy makers to actively engage in global

initiatives to address issues including income disparity, education gap, gender discrimination, climate degradation, and so on, see UNSDGs for details [65].

Academics: Educational Institutions


observed undesirable effects of educational experience on values and perceived end states, educational institutions must revisit selection, assessment, development and training criteria of students, as well as educators, and administrative staff. Another issue pertains to common belief that TBL only relates to business (rather than other fields), a misconception that greatly undermines its integration, teaching and relevance for other disciplines e.g., engineering and natural sciences. To this date, much less is known about the implications of TBL for above-mentioned disciplines, a knowledge gap that requires immediate attention. More so, educators across all fields must adopt a holistic institutional approach to establish the relevance and significance of TBL philosophy in their respective paradigms. Role plays, simulations games, cross-disciplinary internships and TBL case competition are some feasible ways to develop awareness of how to effectively integrate TBL in each study discipline [33], [64].

Business Leaders: Commercial Entities

Past literature in environmental management supports that it is critical for organizations to place greater emphasis on attracting young talent with cognitive inclination towards TBL initiatives e.g., ISO14001 certifications, environmental management and audit systems (EMAS), green manufacturing, clean production, eco-innovation and construction. By making use of globally popular 360 degrees multi-source feedback system, organizations can gather valuable information to redefine selection, assessment, training and development. As a job pre-requisite, organizations are expected to formalize critical assessment of ethical awareness and moral identity for existing and new talent to sustain TBL initiatives such as, community investment projects, income distribution, fair pay, decent treatment, human rights, and green production. Some available techniques with proven benefits for organizations to screen out potential candidates include, but are not limited to simulations, multi-stage interview process, job samples and assessment centers [64].

Theoretical Contributions

Though an extension of work conducted by Piper et al. [20] and Meng et al. [21], the authors have developed a new perspective in business ethics research, particularly TBL. By combining micro-level antecedents (demographics and values) with TBL, this study creates a conceptual link between theories of values in the micro-foundation of CSR [2], education ethics [39], [49], and TBL [20], [37]. Of studies that examine student perception of TBL, the current literature identifies a number of limitation such as, context (Canadian), narrow focus on (business students), and small sample size [32], [63]. This study addresses these issues to a satisfactory level by examining underreserached Asian context (China), comparison of business and engineering students, and a larger sample size. Beyond extending John Elkington’s concept to natural sciences, this is the first study to our knowledge that opens up potential avenues for academics in natural sciences and business to initiate collaborative research to unwrap the unknown implications of TBL for fields beyond business e.g., engineering, civil, mechanical, electronic, etc.

Limitations and Future Directions



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Figure 1. Conceptual framework for relationships of demographics, values and triple bottom-line
Table 1. Mean, Standard Deviation and Correlations.
Table 4. T-values (Sig.) in independent two-Sample t – test.
Table 5. T-test for Difference (Materialist vs. Non-materialist).


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