Journal of Business Ethics

, Volume 116, Issue 3, pp 529–552

Falling or Not Falling into Temptation? Multiple Faces of Temptation, Monetary Intelligence, and Unethical Intentions Across Gender

Authors

    • Department of Management and Marketing, Jennings A. Jones College of BusinessMiddle Tennessee State University
  • Toto Sutarso
    • Division of Information TechnologyMiddle Tennessee State University
Article

DOI: 10.1007/s10551-012-1475-3

Cite this article as:
Tang, T.L. & Sutarso, T. J Bus Ethics (2013) 116: 529. doi:10.1007/s10551-012-1475-3

Abstract

We develop a theoretical model, explore the relationship between temptation (both reflective and formative) and unethical intentions by treating monetary intelligence (MI) as a mediator, and examine the direct (temptation to unethical intentions) and indirect (temptation to MI to unethical intentions) paths simultaneously based on multiple-wave panel data collected from 340 part-time employees and university (business) students. The positive indirect path suggested that yielding to temptation (e.g., high cognitive impairment and lack of self-control) led to poor MI (low stewardship behavior, but high cognitive meaning) that, in turn, led to high unethical intentions (theft, corruption, and deception). Our counterintuitive negative direct path revealed that those who controlled their temptation had high unethical intentions. Due to the multiple faces of temptation (the suppression effect), maliciously controlled temptation (low cognitive impairment and high self control) led to deviant intentions. Subsequent multi-group analysis across gender (a moderator) reformulated the mystery of temptation: a negative direct path for males, but a positive indirect path for females. For males, the negative direct path generated a dark impact on unethical intentions; for females, the positive indirect path did not, but offered great implications for consumer behavior. Both falling “and” not falling into temptation led to unethical intentions which varied across gender. Our counterintuitive, novel, and original theoretical, empirical, and practical contributions may spark curiosity and add new vocabulary to the conversation regarding temptation, money attitudes, consumer psychology, and business ethics.

Keywords

Temptation (impulsive behavior, cognitive impairment, self-control, social moral value, and getting rich)Monetary intelligence (motive, stewardship, meaning)Deviant intentions (theft, corruption, deception)Reflective versus formativeGenderLove of MoneyEvilMoney EthicConsumer psychologyTheory of free will Business ethicsLongitudinal

Those who want to get rich are falling into temptation and a trap and into many foolish and harmful desires, which plunge them into ruin and destruction. For, the love of money is the root of all evils. (1 Timothy 6: 9–10)

For the past several decades, we have witnessed numerous cases of corruption, scandals, and unethical behaviors involving large corporations (Enron, Worldcom) and individuals (Bernie Madoff) (Ashforth et al. 2008; Gino et al. 2011). Deviant behaviors have harmful effects on individuals, organizations, and the large society. Approximately 5 % of global annual revenues, more than $2.9 trillion, was lost due to various forms of corruption or unethical behaviors (Association of Certified Fraud Examiners 2010). This is a worldwide phenomenon that deserves researchers’ attention (Fisman and Miguel 2007; Kish-Gephart et al. 2010; Tang et al. 2011). Due to its pervasive impact, researchers attempt to identify plausible reasons behind these unethical and deviant behaviors (Christian and Ellis 2011).

According to the theory of planned behavior (TPB, Ajzen 1991), attitudes toward the behavior, subjective norm, and perceived behavioral control predict behavioral intention that, in turn, predicts behavior. Researchers have examined TPB in many fields (Armitage and Conner 2001; Cordano and Frieze 2000; Manning 2009) and the relationship between temptation and addictive behaviors, such as eating (Hofmann et al. 2007, 2010), drinking (Collins et al. 2000; Maddock et al. 2000), smoking (Hudmon et al. 1997), and gambling (Holub et al. 2005); consumer behavior (Baumeister et al. 1994, 2008); and more recently, unethical behaviors (Mead et al. 2009; Restubog et al. 2011; Smith et al. 2005; Tenbrunsel 1998). The contribution of TPB to our understanding of the temptation to unethical intentions relationship is not as ubiquitous as most researchers once thought, however.

The theory of free will (Baumeister et al. 1994, 2008) suggests that people value self-control, follow rules, and make intelligent and rational decisions. “Self-control is the psychological capacity that enables individuals to enact behaviors that are consistent with their long-term goals (e.g., of being an ethical person) and refrain form engaging in behaviors that are driven by short-term selfish motives” (Gino et al. 2011, p. 192). The lack of self-control is associated with impulsive behavior and cognitive impairment. In our culture, there are “many rules and standards, including moral rules to which individuals must conform” (Mead et al. 2009, p. 594). Strong ethical standards (the Ten Commandments and honor code) curb unethical behavior intentions (Ariely 2008; Tang 2012). Rational choice is directly related to getting the most bang for the money (Mickel and Barron 2008) and selecting the best products (Baumeister et al. 2008). Very little research has combined the fields of consumer behavior, the psychology of money (monetary intelligence), and business ethics to investigate the temptation to unethical intentions relationships.

Our present study attempts to fill the void. We adopt the theory of free will (consumer behavior; Baumeister 2002; Baumeister et al. 1994, 2008) as the foundation of our major theoretical framework and apply the notion of temptation (TPB; Ajzen 1991) in the context of unethical intentions (business ethics; Chen and Tang 2006; Tang and Chiu 2003). We propose a theoretical measurement model that (1) getting rich (affective), (2) impulsive behavior (behavioral), and (3) cognitive impairment (cognitive), i.e., the ABC of an attitude, as well as (4) social moral values (subjective norm) and (5) loss of self-control (perceived control) are components of temptation that lead to two consequences—becoming “selfish” and deviating from important “goals” (Gino et al. 2011, p. 192). We develop a theoretical structural equation (SEM) model (Fig. 1), explore the relationship between temptation and deviant intentions, treat monetary intelligence (MI) (psychology of money—motives, stewardship, and meaning of money, Tang 1992; Tang and Chiu 2003; Tang et al. 2012b) as a mediator and gender as a moderator, and investigate the direct and indirect paths simultaneously based on multiple-wave panel data collected from 340 part-time employees who are also university students in a business class.
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Fig. 1

A theoretical model of temptation, MI, and unethical intentions

The reflective temptation construct has five significant sub-constructs, whereas the formative model offers some novel insights: High levels of impulsive behavior, cognitive impairment, and lack of self-control and low levels of social moral values and getting rich define temptation that, in turn, is related to becoming selfish and overlooking important goals. We explore two parsimonious SEM models of temptation (reflective vs. formative): The positiveindirect path (Paths 2 and 3) suggests that falling into temptation leads to poor MI (low stewardship and high cognitive meaning of money) that, in turn, entices them to have high deviant intentions. Our counterintuitive negativedirect path (Path 1) shows that those who do not fall into temptation have high theft, corruption, and deception intentions. The overall impact is negative: Maliciously controlled temptation is significantly related to unethical intentions. Our subsequent multi-group analyses across gender reformulated the mystery of temptation—a negative direct path for males, but a positive indirect path for females. For males, the overall dark impact of temptation on unethical intentions is substantial, causing grave concerns; for females, the overall dark impact is trivial, but offers great implications for consumer behavior. Our counterintuitive novel findings make significant theoretical, empirical, and practical contributions (Colquitt and Zapata-Phelan 2007), spark curiosity, and add new vocabulary to the conversation regarding temptation, money attitudes, consumer behavior, and unethical behavior intention in the literature.

Theory and Hypotheses

Temptation: Construct Conceptualization

According to Locke (1969, p. 334), the first question a scientific investigator must ask is not “how can I measure it?” but rather, “what is it?” In order to understand the construct clearly and achieve a solid construct conceptualization, researchers must use specific, accurate, and explicit terms and define the conceptual construct precisely in a positive direction without circular or tautological argument (Edwards and Bagozzi 2000; MacKenzie et al. 2011). We define temptation below.

What is Temptation?

From the Greek word Peirasmos, temptation is the state of being enticed, allured, or seduced. It carries two meanings—being misled into sin or enticed to do wrong, or being put to the test. We approach the temptation construct from the perspectives of consumer behavior and business Ethics. First, consumers’ desire to perform an act (consumption) leads to instant gratification (Tice et al. 2001), but causes great regret or guilt later. Second, when tempted, most people are willing to be a little dishonest, regardless of the risks. People rationalize their dishonesty easily when cheating is one step removed from cash (Ariely 2008). It is the weak temptation, as compared to strong temptation, that has an inhibiting effect on self-regulation process, forming a bigger threat for long-term goal attainment (Kroese et al. 2011). People’s temptation to break the simple, small rules is titillating because it temporally brings a sense of excitement to life and can be rationalized easily. This is the reason why so many people are easily enticed to eat chocolate, shop spontaneously, and do bad, deviant, and unethical things. Resisting temptation, on the other hand, takes a lot of willpower, clear thinking, and self-control that may or may not deliver us from evil.

Components of Temptation

A key to understanding the motivational mechanisms of deviance lies in theories of self-regulation (Christian and Ellis 2011). Deviant behaviors are volitional, but are different from crimes of passion (due to sudden unexpected impulses) and impulsive behavior/consumption. Following TPB, the theory of free will (Baumeister 2002; Baumeister et al. 1994, 2008), and the ABC model of an attitude (Bagozzi et al. 1979), we define temptation as a multi-dimensional individual difference variable with five components: (1) getting rich, (2) impulsive behavior, (3) cognitive impairment, (4) social moral values, and (5) lack of self-control. The entity to which it applies is people. We discuss these constructs below.

Getting Rich (Affective)

Why do people (e.g., CEO/CFO of Enron and Bernie Madoff) fall into temptation and engage in unethical behaviors? Enron’s executives were provided with substantial bonuses in the form of stock options. Given the size of the bonus payments, the “temptation” to engage in unethical behavior was, in hindsight, disturbingly obvious (The Daily Record2003). When tempted, most are willing to be a little dishonest and to do whatever it takes to become rich. Getting rich is a highly emotional, affective aspect of people’s money attitudes. Those who want to get rich will take risks and engage in unethical behaviors (Tang et al. 2008a, 2011).

Impulsive Behavior (Behavioral)

Those who fall into temptation follow their hearts, seek instant gratification (Tice et al. 2001), and act in an impulsive and spontaneous way. People suddenly have an urge to do something, act on that impulse without carefully or thoroughly considering whether it is consistent with their long-range goals, ideals, and plans (Baumeister 2002). Most impulses are resistible, yet sometimes prove irresistible when their self-control has failed (Rook 1987). Some opportunistic people may capture the moment and engage in unethical behaviors when opportunities present themselves in the environment.

Cognitive Impairment (Cognitive)

Comparing three types of theories regarding how people restrain impulses and override incipient responses—willpower and strength, cognitive processes, and self-control as a skill—Baumeister (2002) supported the willpower and strength model. Sleep deprivation causes workplace deviance due to the depletion of self-regulatory resources (Christian and Ellis 2011). When crucial self-regulatory resources have been depleted, people without a “strong will” become weak physically, psychologically, and spiritually, and experience cognitive impairment. Due to temptation, people become disoriented and lose their abilities to concentrate on important, long-term goals.1 However, executives in recent scandals strategically planned, cleverly organized, deceitfully misled, and carefully controlled/executed their unethical act (theft, corruption, and deception) with concerted efforts and executive function. These scandals are not caused by the executives’ lack of “intelligence” or “brains,” nor accidents, honest mistakes, or cognitive impairment, but rather by their self-interests, malicious intent, and lack of “wisdom,” “virtue” (Feiner 2004, p. 85; Tang and Liu 2012). We posit that most people engage in unethical behaviors to fulfill their specific, selfish, and strategic and intentional purposes which are quite different from consumers who yield to temptation and buy impulsively at shopping malls. In other words, compared to CEO/CFO of Enron and Bernie Madoff, mentally challenged individuals may not have the intellectual competencies to execute unethical behaviors.

Lack of Self-Control (Perceived Control)

Self-control is “the ability to override or change one’s inner responses, as well as to interrupt undesired behavioral tendencies (such as impulses) and refrain from acting on them” (Tangney et al. 2004, p. 274). When people lose track of their behavior, they experience a self-control breakdown. People in a sad mood eat unhealthy snack foods more than those without emotional distress. “When people are upset, they indulge immediate impulses to make themselves feel better, which amounts to giving short-term affect regulation priority over other self-regulatory goals” (Tice et al. 2001, p. 53). Acts of self-regulation without rest or replenishment (Muraven and Baumeister 2000) “impair subsequent self-regulatory efforts” (Gino et al. 2011, p. 192). Self-control is the poorest among people who have performed a prior act of self-control. People who are on a diet tend to eat more pieces of candy when given the opportunity in an experiment than those who are not. Further, both traits self-control and self-control depletion predicted impulsive cheating behavior on a problem-solving task (Baumeister et al. 1998; Mead et al. 2009; Muraven et al. 2006; Rosenbaum 1993). People with high self-control have less aggressive behavior (Latham and Perlow 2006) and lower deviant behaviors (Bordia et al. 2008). In a “cold” non-visceral state, the presence of temptation prompts cognition to support self-control, whereas in a “hot” visceral state, temptation prompts the same cognitive processes to support impulsive behavior (Nordgren and Chou 2011). Thus, some coldhearted individuals seize the opportunity to become corrupt and engage in unethical behaviors for financial gains, but do not do it impulsively to make themselves feel better (cf. Tice et al. 2001). As mentioned, people’s decisive unethical behaviors reflect their strong self-control and executive function. That is, they do it on purpose. It is not an accident.

Social Moral Values (Subjective Social Norm)

Getting Harvard, MIT, Yale, and Princeton students to contemplate their own ethical values by “recalling the Ten Commandments or signing an honor code” eliminates cheating completely, while offering “poker chips” to redeem for cash, a few seconds later, doubles the level of cheating (Ariely 2008, p. 24; Aquino et al. 2009; Tang 2012). With a high level of supervisory guidance, a high (or low) level of behavioral integrity (Simons 2002; Simons et al. 2007) curbs (or incites) deviant behavior (Dineen et al. 2006). People with a high love of money and low perceptions regarding the authenticity of a supervisor’s personal integrity and character (ASPIRE) had the highest unethical behavior intention, whereas those with a high love of money and high ASPIRE had the lowest (Tang and Liu 2012). Thus, the supervisor’s authentic personal integrity and character (ASPIRE) is a moderator and makes a difference. There are several important implications: Most people’s ethical intentions and behaviors are influenced by ethical values and cultures at the individual and organization levels (Kish-Gephart et al. 2010; Weiss et al. 2010). The Ten Commandments and poker chips signify sacred and secular values, respectively. Temptations presented positively or negatively in the social context contribute to individuals’ ethical or unethical intentions. Taken together, we assert that these five sub-constructs make significant and independent contributions to our theoretical measurement model of temptation.

Relationships Between Constructs and Measures (Reflective vs. Formative)

We discuss the nature of the relationships between the constructs and measures below. For decades, most researchers in social sciences have used a reflective model for attitudinal constructs rather than a formative model (Edwards and Bagozzi 2000). Recent developments in measurement theory and application led some researchers to reconsider constructs, such as job satisfaction, not as a reflective model, but as a formative model—a composite or aggregate of the satisfaction with pay, promotion, supervisor, coworkers, and the work itself (Williams et al. 2003). Further, some scholars strongly advocated the use of the formative measurement model and suggested that paths emanating from a misspecified construct may lead to Type I errors, whereas paths leading to a misspecified construct may lead to Type II error (Jarvis et al. 2003; MacKenzie et al. 2005, 2011). Others expressed concerns regarding its merits (Edwards 2011). We describe and compare both reflective and formative models of temptation next.

Reflective Model

We treat the five sub-constructs or factors as an imperfect reflection of the underlying latent construct—temptation. The indicators and the first-order latent factors are viewed as manifestations of the overall focal construct; the focal construct exists separately at a deeper and more embedded level than its first-order factors and items; and, a change in the focal construct would be expected to produce a change in all of its factors and items. The indicators and first-level sub-constructs are best thought of as reflective of the focal construct. The direction of the relationship flows from the latent construct to the indicators. Direct manipulation of a particular indicator will not have an effect on the latent variable. It is appropriate when a researcher is interested in measuring a stable focal construct over time or across situations, or has several randomly selected parcels of items, each of which is reflective of a focal construct.

Formative Model

We treat items and the five first-order sub-constructs (factors) as a “reflective” model and consider the five sub-constructs as distinguishable perspectives, defining characteristics, or “formative” indicators, of temptation. The elimination of any single sub-construct will restrict the overall construct in a significant way. The non-interchangeable sub-dimensions (antecedents) formulate the temptation construct that, in turn, is related to two or more items or reflective measures that capture the overall construct or various consequences (outcomes). The patterns for the formation and consequence of temptation depend on different outcomes involved in the analyses. [Our reflective and formative models of temptation (with results of the present study) are presented in Figs. 2 and 3, respectively, and Appendix.]
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Fig. 2

Results of the temptation scale—a reflective model

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Fig. 3

Results of the temptation scale—a formative model

After discussions of the fallacy of formative measures, Edwards (2011) proposed alternatives to formative measurement. Our model (presented in Fig. 3) actually fits the description—an alternative to the conventional formative measurement model that “avoids” the shortcomings of formative measurement (Edwards 2011). It is a “model that replaces formative measures with facet constructs and multiple reflective measures” (see Fig. 6, Edwards 2011, p. 384). In this case, “the construct is nothing more than a label for its dimensions considered collectively” (p. 384). In summary, we establish a temptation measure (as a trait) and explore the validity in a theoretical SEM model.

Step 1: To achieve model identification, a formative construct must emit paths to (1) at least two unrelated latent constructs with reflective indicators, (2) at least two theoretically appropriate reflective indicators, or (3) one reflective indicator and one latent construct with reflective indicators (Jarvis et al. 2003). Step 2: In order to establish the validity (nomological network of correlations) of the temptation construct, we adopt two models of temptation (i.e., reflective vs. an alternative to conventional formative measurement) in two separate analyses and select two additional outcome items (Items 18 and 19, Fig. 4) and two additional constructs—unethical intentions (PUB) (reflective) and MI (formative)—for two reasons. First, the temptation construct taps directly and indirectly on both constructs that are content-valid measures. Second, we treat MI as a mediator and examine the direct path (temptation → unethical intentions) and the indirect path (temptation → MI → unethical intentions) simultaneously. Since we treat MI as a formative measurement model, we also included two additional outcome variables (Machiavellianism) (Tang and Chen 2008; Tang and Tang 2010).
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Fig. 4

Results of our theoretical model involving temptation (reflective), MI, and unethical behavior intentions (the whole sample)

Unethical Behavior Intentions

It is impossible to directly measure managers’ actual corruption or unethical behaviors because most behaviors are performed in private, except in formal criminal investigations of corruption cases, police records (e.g., Fisman and Miguel 2007), and laboratory experiments (Ariely 2008). However, people are willing to provide accurate information for specific questions in an anonymous survey (Richman et al. 1999; Schoorman and Mayer 2008). The convergence of the incumbent’s self-report and the coworker’s peer report on counterproductive behavior suggests that self-reported unethical intention is a reasonable surrogate measure of behavior (De Jonge and Peeters 2009; Fox et al. 2007; Martin et al. 2007).

Among workplace deviance (Bennett and Robinson 2000), counterproductive behavior (Cohen-Charash and Spector 2001; Spector and Fox 2010), corruption, and misbehavior, researchers have examined the propensity to engage in unethical behaviors (PUB) (Tang and Chiu 2003) that are a subset of organizational deviances performed against organizations (Robinson and Bennett 2000). The PUB scale includes theft, corrupt intent, and deception. The corrupt intent sub-scale involves the misuse of position, power, or authority for personal or organizational gain (receiving gifts, money, bribery, and kickbacks); acts committed against the company (sabotage and theft); and acts conducted on behalf of the organization (laying off employees for personal gain) (Ashforth et al. 2008; Robinson and Bennett 2000). These constructs have been tested empirically in China (Du et al. 2007), Hong Kong (Tang and Chiu 2003), Macedonia (Sardžoska and Tang 2009, 2012), the US (Piffa et al. 2012), and more than 31 geopolitical entities/countries across six continents (Tang et al. 2011) and cited in review articles (e.g., Kish-Gephart et al. 2010) and textbooks (Bateman and Snell 2013).

Temptation to Unethical Behaviors

We focus on the direct path between temptation and unethical intentions (Path 1). One of the real root causes of the corporate scandals is “the overemphasis American corporations have been forced to give in recent years to maximizing shareholder value without regard for the effect of their actions on other stakeholders” (Kochan 2002, p. 139). Profit-based mechanisms create a huge amount of pressure and opportunity for managers and have serious flaws. Enron’s executives were provided with substantial bonuses in the form of stock options—a temptation—that might have caused executives to deceptively manipulate accounting procedures by cooking the books and intentionally engage in unethical behaviors (The Daily Record2003; Kennedy and Lawton 1993). As mentioned, scandals and unethical behaviors in the US and around the world are caused by executives’ “intentional actions” and are “not” accidents or honest mistakes. They did it on purpose and not due to cognitive impairment and/or lack of self-control, in particular. High love-of-money individuals have high Machiavellianism and a high risk tolerance (Tang et al. 2008a, b). Domain-specific temptation explained 40 % of the unique within-individual variance in impulsive behavior (Tsukayama et al. 2012). On the basis of the ancient wisdom (those who want to get rich are falling into temptation and the love of money is the root of all evils) and empirical research findings, we test Hypothesis 1 below.

Hypothesis 1

Temptation is directly related to unethical behavior intentions.

Monetary Intelligence (MI)

For the past three decades, researchers have examined numerous money-related attitudes and measures (Furnham 1984; Furnham and Argyle 1998; Mitchell and Mickel 1999; Srivastava et al. 2001; Yamauchi and Templer 1982). Among them, the money ethic (MES, Tang 1992) or the love-of-money construct, a subset of MES (Tang and Chiu 2003; Tang and Chen 2008; Tang et al. 2006, 2011), has become one of the most cited and systematically used constructs of money attitude in the literature (Mitchell and Mickel 1999). It is mildly related to materialism (Belk 1984, 1985, 1988; Kasser 2002), differs from greed (Cozzolino et al. 2009), is related to a winner-take-all mentality—the Matthew effect (Merton 1968; Tang 1996),2 and predicts voluntary turnover (Tang et al. 2000) and unethical behavioral intention in multiple-wave panel studies (Tang and Chen 2008; Tang and Liu 2012). This construct has been substantiated in empirical studies across almost three dozen entities around the world (Du et al. 2007; Gbadamosi and Joubert 2005; Lim and Teo 1997; Nkundabanyanga et al. 2011; Singhapakdi et al. 2012/forthcoming; Tang et al. 2006, 2008b, 2011, 2012a; Vitell et al. 2006; Wong 2008) and cited in influential reviews (Kish-Gephart et al. 2010; Lea and Webley 2006; Mickel and Barron 2008; Mitchell and Mickel 1999; Zhang 2009) and in numerous books (Colquitt et al. 2011; Furnham and Argyle 1998; McShane and Von Glinow 2008; Milkovich et al. 2010; Rynes and Gerhart 2000).

Based on previous research (Tang 1992, Tang and Chen 2008; Tang and Chiu 2003), MI is defined as a multi-dimensional individual difference variable that involves people’s ability to process and appraise monetary motive (affective), regulate money-related intentions or behaviors (behavioral), and prioritize its cognitive importance (cognitive) to promote personal growth, happiness, or subjective well-being (Tang et al. 2012b). MI (money smart) is a grand umbrella construct with three sub-constructs—the affective motive (rich, motivator, and importance), the behavioral stewardship of money (make, budget, donate, and contribute), and the cognitive meaning (happiness, respect, achievement, and power). Results based on 6,586 managers in 32 geopolitical entities across six continents showed that low motive, high stewardship, and high meaning define MI that is related to higher pay satisfaction than life satisfaction. The formation and consequence of MI varied across age, gender, and economic development, providing intrapersonal, interpersonal, and cross-cultural differences—becoming good stewards and focusing on what we do with our money, actually contribute significantly, positively, and consistently to MI and to job and life satisfaction. When the cognitive meaning of money is (is not) a prominent makeup of MI, people tend to have higher (lower) pay satisfaction than life satisfaction. These findings seem to support the ancient wisdom, “Poverty consists, not in the decrease of one’s possessions, but in the increase of one’s greed” (Plato, 427–347 BC). “Whoever loves money never has money enough; whoever loves wealth is never satisfied with his income” (Ecclesiastes, 5: 10). We explore MI as a mediator in the present study.

Monetary Intelligence (MI) as a Mediator

Temptation to MI (Path 2)

Materialism (Belk 1984) leads to the dark side of the American dream (Arndt et al. 2004; Kasser 2002; Kasser and Ryan 1993; Mick 1996; Tang 2007; Tang et al. 2012a/forthcoming). Subject to all forms of temptation, materialistic consumers have high financial worries, poor money-management skills, and a great tendency toward compulsive buying and over spending, i.e., low MI/money smart (Gardarsdottir and Dittmar 2012). After controlling for income and money-management skills, materialism is directly related to the amount of debt. Students on five college campuses reported an average debt of $1,035 (SD = $1,849). Those with greater debt reported greater stress and decreased financial well-being (Norvilitis et al. 2006). The US saving rates in 2006 dropped to an all time low at “−.5 %” since the great depression (Associated Press 2006). Only 14 % of Americans have confidence in their ability to retire comfortably (Helman et al. 2012). People lose track of their self-control, become cognitively impaired, fall into temptation, and spend their money impulsively (Baumeister 2002). Choices made after losses are riskier than those after gains (Gehring and Willoughby 2002). Following a vicious cycle, temptation is related to poor MI (lower stewardship of money and higher value toward the enjoyment of having money). We test our Hypothesis 2 as follows:

Hypothesis 2

Temptation is related to MI.

MI to Unethical Intentions (Path 3)

The affective component of money attitude is associated with deviant behaviors and unethical intentions (Kish-Gephart et al. 2010; Tang and Chen 2008; Tang et al. 2011). Money is often associated with the psychological meaning of achievement and recognition, status and respect, freedom and control, and power (Mitchell and Mickel 1999; see Colquitt et al. 2011). Considering money as a sign of their achievement leads to low satisfaction with pay and life (Fishbach et al. 2003; Srivastava et al. 2001; Tang 1992, 2007). Pay dissatisfaction causes people to become corrupt in the name of justice (Greenberg 1993), equity (Gino and Pierce 2009a, b), revenge (Ashforth and Anand 2003), or retaliation (Skarlicki and Folger 1997). Those who do not manage their money carefully (Dew and Xiao 2011; Mickel et al. 2003) have many foolish and harmful desires, which plunge them into ruin and destruction.

Hypothesis 3

MI is related to unethical intentions.

It is plausible that our direct path and indirect path may be operated differently based on our theoretical model. Suppression occurs when “the indirect effect” has “the opposite sign of the direct effect” (Shrout and Bolger 2002, p. 430) which explains why a theoretically interesting relation is not strong. That is, the direct and indirect effects of similar magnitudes and opposite signs result in a non-zero and non-significant overall relationship. We challenge the assumption that temptation leads to the dark side of unethical intentions consistently (Hypothesis 1) and argue that due to our positive indirect effect (suppression effect, Hypotheses 2 and 3), temptation may not have a strong and negative relationship with unethical intentions for all participants. “A moderator is a qualitative (e.g., sex, race, class) or quantitative (e.g., level of reward) variable that affects the direction and/or strength of the relation between an independent or predictor variable and a dependent or criterion variable” (Baron and Kenny 1986, p. 1174). We treat gender as a moderator and test our model using multi-group analysis (Amos).

Gender

Males have higher concerns for money and career advancement than ethical values (Beu et al. 2003; Deshpande 1997; Hoffman 1998) when compared to females. Ethics training may have limited effects for females, but no effect for males (Conroy and Emerson 2004; Ritter 2006; Traiser and Eighmy 2011). The top business schools not only fail to improve the moral character of students, but also actually weaken it (Schneider and Prasso 2002). Students who take a single semester of introductory economics show a significant decline in honesty and increase in self-interest (Frank et al. 1993). Highly educated executives in recent scandals received their training at the best business schools (Merritt 2002). Machiavellianism mediates the relationship between the love of money and unethical intentions for business students, but not for psychology students; for male students, but not for female students; and for male business students, but not for female business students (Tang and Chen 2008). Male students are more unethical than female students.

Hypothesis 4

The dark impact of temptation on unethical intentions is stronger for males than for females.

Method

Procedure

The first author collected data from 340 students (male = 221, 65.0 %; female = 119, 35.0 %; return rate = 95 %) who took a management class in the college of business, accredited by AACSB-International, at a state university in the southeastern US for 4 years. In a 16-week semester, students completed eight two-page (on one sheet of paper) surveys and other activities for course credits, confidentially with initials and the last four digits of their social security number in order to match these eight-panel survey data. Participants completed these surveys at least 1 or 2 weeks apart in the semester. This procedure avoids the possible impact of fatigue/memory, common method variance (CMV) bias, and enhances the psychological separation of predictors and criteria (Podsakoff et al. 2003). The professor was blind regarding students’ survey results and debriefed the purposes of this study at the end of the semester.

Measures

We adopted our 15-item, 5-factor temptation scale; the 30-item, 10-factor MI scale (MI, Tang 1992; Tang et al. 2012b); 4-item Machiavellianism (Mach IV, 4 items, two items from tactics and two items from views of human nature, Christie and Geis 1970; Tang and Chen 2008); and three sub-constructs (theft, corruption, and deception) of the 15-item, 5-factor propensity to engage in unethical behavior scale (PUB) (Chen and Tang 2006; Tang and Chiu 2003) (see Appendix). We used a 5-point Likert scale with strongly disagree (1), disagree (2), neutral (3), agree (4), and strongly agree (5) as anchors for temptation, MI, and Machiavellianism measures. For the PUB scale, we used a different set of anchors: very low probability (1), low probability (2), average (3), high probability (4), and very high probability (5) and provided the following instructions: If you were given the opportunity in your work environment, what is the probability that you may engage in the following activities. It is a measure of self-prediction. We also collected demographic variables (e.g., gender, age, years of education, current job tenure, and income) and many other filler items. We used (SPSS/Amos) and the following criteria for configural invariance (passing 5 out of 6 criteria): (1) Chi-square and degrees of freedom (χ2/df), (2) incremental fit index (IFI > .90), (3) Tucker–Lewis index (TLI > .90), (4) comparative fit index (CFI > .90), (5) standardized root mean square residual (SRMSR < .10), and (6) root mean square error of approximation (RMSEA < .10) (Vandenberg and Lance 2000). We achieve metric invariance when the differences between unconstrained and constrained multi-group confirmatory factor analyses (MGCFAs) are not significant (ΔCFI, ΔRMSEA ≤ .01, Cheung and Rensvold 2002). All measures in the present study were collected at least 1 week apart, for some more than 2 months apart.

Results

Descriptive Statistics

The means, standard deviations, Cronbach’s α, and correlations of demographic variables, temptation, five sub-components of temptation, MI, and unethical intentions for the whole sample are presented in Table 1. All five sub-constructs of temptation were significantly correlated. Cronbach’s α and composite reliability for temptation were .81 and .81, respectively (Table 1).3 Age was significantly correlated with years of education, job experience, and income. Income was also associated with levels of education and job experience. MI was related to the sub-construct of social moral values. Unethical intentions were related to gender (male), low temptation, low cognitive impairment, and strong self-control.
Table 1

Mean, standard deviation, Cronbach’s α, composite reliability, and correlations of variables

Variable

M

SD

1

2

3

4

5

6

7

8

9

10

11

12

13

1. Age

23.64

5.63

             

2. Sex (%male)

.65

.48

−.04

            

3. education (yr.)

15.33

1.39

.40**

−.04

           

4. Job (yr.)

3.31

8.21

.44**

.03

.06

          

5. Income ($)

23,678.19

52,329.77

.28**

.05

.20**

.17*

         

6. Temptation

3.53

.56

−.04

−.02

−.02

.01

−.08

        

7. T-Spontaneous

3.67

.71

−.03

−.07

.01

.01

−.09

.70**

       

8. T-Impaired

3.10

.95

−.05

−.00

−.06

−.00

.10

.79**

.46**

      

9. T-Control

3.52

.86

−.05

−.06

−.05

−.01

−.07

.76**

.45**

.54**

     

10. T-Moral

3.75

.71

−.07

.03

−.00

−.01

.08

.55**

.26**

.30**

.29**

    

11. T-Rich

3.61

.89

.03

.02

.05

.03

−.06

.59**

.27**

.28**

.25**

.12*

   

12. MI

3.62

.55

−.14

−.00

−.08

.00

−.04

.08

−.01

.04

.08

.17**

.02

  

13. Unethical

1.41

.54

.05

.19**

−.08

−.04

.04

−.13*

−.04

−.14*

−.13*

−.06

−.06

.04

 

Cronbach’s α

       

.81

.51

.75

.75

.44

.71

.90

.87

Composite reliability

       

.81a

       

N = 340. Gender: male = 1, female = 0. MI = monetary intelligence

p < .05, ** p < .01

aComposite reliability for temptation (formative model, Fig. 3, based on results of reflective model, Fig. 2) = [(sum of standardized loading)2/{(sum of standardized loading)2 + sum of indicator measurement error}]. [Indicator measurement error = 1 − (standardized loading)2]

The Temptation Scale (Reflective vs. Formative)

For our 15-item, 5-factor temptation scale, we selected two additional items to achieve model identification for our formative model (Jarvis et al. 2003). These items depicted not only two consequences of temptation—becoming “selfish” (Item 16, see Appendix) and deviating from important “goals” (Item 17) (Gino et al. 2011)—but also the overall notion of temptation. The direction of the relationship flows from temptation to sub-constructs for our reflective model, but from sub-constructs to temptation for the formative model.

Our formative model (Fig. 3: χ2 = 190.73, df = 104, p < .001, χ2/df = 1.83, IFI = .95, TLI = .93, CFI = .95, SRMSR = .04, RMSEA = .06) was better than the reflective model (Fig. 2: χ2 = 237.82, df = 114, p < .001, χ2/df = 2.09, IFI = .92, TLI = .91, CFI = .92, SRMSR = .05, RMSEA = .06). The differences between the two were significant (i.e., Δχ2 = 47.09, Δdf = 10, p < .001; ΔCFI = .0249 > .010). For our reflective model, the descending order of regression weights (factor loadings) for the five sub-constructs were as follows (Fig. 2): impulsive behavior (.86), cognitive impairment (.83), self-control (.82), social moral value (.48), and getting rich (.31), respectively. For the formative model, the paths were .49, .32, .32, −.23, and −.16, respectively. In both models, all regression weights and paths were significant. For the formative model, the highest correlation among the five sub-constructs was between impulsive behavior and cognitive impairment (.74) which was smaller than .80 (Kim 2011). These five non-interchangeable sub-constructs are relatively independent and make significant and different contributions to the temptation construct. High correlations among the sub-constructs provide high reliability for the overall reflective temptation construct, whereas low correlations among the sub-constructs reveal independent contributions to the same overall formative construct (Edwards 2011).

Measurement Invariance

We examined measurement invariance of our temptation scale across gender using our reflective model (Fig. 3). First, regarding configural (factor structure) invariance, the fit between our measurement model and our data for the male sample (χ2 = 156.21, df = 104, p < .0007, χ2/df = 1.50, IFI = .95, TLI = .93, CFI = .95, SRMSR = .05, RMSEA = .05) was slightly better than that for the female sample (χ2 = 160.39, df = 104, p < .0003, χ2/df = 1.54, IFI = .92, TLI = .89, CFI = .91, SRMSR = .07, RMSEA = .07), due to the different sample size (males = 221 vs. females = 119). Second, we checked metric (factor loading) invariance using a multi-group confirmatory factor analysis (MGCFA) across gender. There was a good fit for the unconstrained model (χ2 = 316.79, df = 208, p < .0000, χ2/df = 1.52, IFI = .94, TLI = .91, CFI = .93, SRMSR = .05, RMSEA = .04). In our constrained MGCFA, we set all the paths from items to the first-order latent constructs to be equal for males and females (χ2 = 330.20, df = 218, p < .0000, χ2/df = 1.51, IFI = .93, TLI = .92, CFI = .93, SRMSR = .05, RMSEA = .04). The differences between unconstrained and constrained MGCFAs were not significant (ΔCFI = ΔRMSEA = .00 ≤ .01). We achieved configural and metric invariance across gender for the temptation scale which gave us confidence to test our theoretical SEM across gender.

Common Method Variance (CMV)

Due to our longitudinal data, CMV should not be a concern (Podsakoff et al. 2003; Spector 2006). Following suggestions in the literature, we adopted Harman’s single-factor test and examined the unrotated factor solution involving 54 items and all three variables of interest in an exploratory factor analysis (EFA) and identified 15 factors, with eigenvalue greater than one. We listed the scale and amount of variance explained (total = 70.29 %) below: MI (16.87 %), PUB (9.72 %), temptation-lack of self-control (7.31 %), MI (5.23 %), temptation-cognitive impairment (4.93 %), temptation-impulsive behavior (3.63 %), MI (3.24 %), temptation-getting rich (3.07 %), temptation-social moral values (2.84 %), and constructs with cross-loadings (2.61, 2.45, 2.33, 2.09, 2.03, and 1.95 %). No single factor accounted for the majority of the covariance in the independent and criterion variables. CMV was not a concern in this research.

Our Theoretical Model

RMSEA tends to over reject a true model due to “small sample size” and “model complexity” (Tang et al. 2006, p. 446). To maintain a large sample size to item ratio and reduce model complexity for the whole sample and subsequent multiple-group analyses across subgroups of gender using our SEM model, we established a parsimonious model using “15” parcels/items—5 parcels for temptation with 2 outcome items, 3 parcels for MI with 2 outcome parcels, and 3 parcels for unethical intentions—instead of “60.” The sample size to item ratio was 23 (340/15 = 22.67). We adopted two different items—Items 18 (plunge men into ruin and destruction) and 19 (corrupt our moral beliefs or ethical standards) (Appendix)—for the temptation construct (reflective vs. formative), appropriate in the business ethics context. We treated MI (Tang et al. 2012b) as a formative measurement with three sub-constructs—affective motive, behavioral stewardship, and cognitive meaning—and two additional outcome parcels (two items each) for the Machiavellianism construct, also appropriate in the business ethics context (Tang and Tang 2010). The reflective unethical intentions construct had three sub-constructs: theft, corrupt intent, and deception (Chen and Tang 2006).

Reflective Model

Our parsimonious theoretical model with a reflective temptation construct (χ2 = 160.12, df = 85, p < .000, χ2/df = 1.88, IFI = .95, TLI = .93, CFI = .95, SRMSR = .06, RMSEA = .05) is presented in Fig. 4. Our counterintuitive, significant, negative direct path revealed that temptation was significantly related to unethical intentions (Path 1 = −.20, p < .003), supporting Hypothesis 1. Our significant, positive indirect path suggested that a high level of temptation was related to poor MI (Path 2 = .15, p < .05) that, in turn, was related to high unethical intentions (Path 3 = .28, p < .001). Hypotheses 2 and 3 were supported. Due to multiple faces of temptation and the suppression effect, the overall impact from temptation to unethical intentions was negative: The standardized total impact (−.158) was the sum of the direct impact (−.200) and the indirect impact (.0428 = .154 * .278). Carefully controlled malicious temptation was related to deviant intentions. Overall, temptation creates a dark impact on unethical intentions for participants in the whole sample. The factor loadings of all five sub-constructs of temptation were as follows: cognitive impairment (.79), lack of self-control (.73), impulsive behavior (.67), social moral values (.37), and getting rich (.35). Stewardship behavior (−.15) and the cognitive meaning of money (.34) contributed to MI. Regarding unethical intentions, corrupt intent (.88) seemed to be more prevalent than deception (.77) and theft (.63).

Males

Multi-group analysis across gender revealed some interesting and profound results (χ2 = 239.06, df = 170, p < .0004, χ2/df = 1.41, IFI = .95, TLI = .94, CFI = .94, SRMSR = .06, RMSEA = .03). For males, the direct path was significant and negative (−.20, p < .05) (see Fig. 5), supporting Hypothesis 1. For the indirect path, temptation was not significantly related to MI (.02, n.s.) that, in turn, was significantly associated with unethical intentions (.22, p < .05), supporting Hypothesis 3, but not Hypothesis 2. MI was not a mediator. The overall indirect impact from temptation to unethical intentions was inconsequentially small (.004 = .02 * .22). Both MI and temptation contributed significantly to unethical intentions. The standardized total impact from temptation to unethical intention was negative [total impact (−.197) = direct impact (−.201) + indirect impact (.004)]. Corrupt intent (.95) had the strongest factor loading, followed by deception (.76) and theft (.64). For males, temptation has a strong dark impact on unethical intentions. The meaning of money contributed significantly (.47, p < .001), while stewardship behavior contributed marginally (−.16, p = .054) to MI.
https://static-content.springer.com/image/art%3A10.1007%2Fs10551-012-1475-3/MediaObjects/10551_2012_1475_Fig5_HTML.gif
Fig. 5

Results of our theoretical model involving temptation (reflective), MI, and unethical behavior intentions (the male sample)

Females

The negative direct path was non-significant (−.172, n.s.), but the positive indirect path was significant (temptation → MI = .341, p < .01; MI → unethical intentions = .480, p < .05) (Fig. 6). MI was a mediator. Results supported Hypotheses 2, 3, and 4, but not Hypothesis 1. The indirect impact from temptation to unethical intentions was substantial (.164 = .341 * .480). The overall standardized total impact from temptation to unethical intention was negative, but trivial [total impact (−.007) = direct impact (−.171) + indirect impact (.164)]. Deception (.91) had the strongest factor loading, followed by corrupt intent (.51) and theft (.39). For females, temptation has a weak dark impact on unethical intentions.
https://static-content.springer.com/image/art%3A10.1007%2Fs10551-012-1475-3/MediaObjects/10551_2012_1475_Fig6_HTML.gif
Fig. 6

Results of our theoretical model involving temptation (reflective), MI, and unethical behavior intentions (the female sample)

MANOVA Results

We checked the mean differences next. Our multivariate analysis of variance (MANOVA) of demographic variables (age, education, job experience, and income) across gender was not significant (F (4, 199) = .73, p > .05, Wilks’ lambda = .986, partial eta squared = .014, power = .233). MANOVA results regarding major variables across gender were significant (F (11, 321) = 2.40, p = .007, Wilks’ lambda = .924, partial eta squared = .076, power = .954). Males had lower stewardship behavior (3.47 vs. 3.67), but higher theft (1.40 vs. 1.22), corruption (1.54 vs. 1.32), and deception (1.52 vs. 1.26) than females.

Formative Model

Results of our SEM model with formative temptation (χ2 = 106.48, df = 74, p < .0080, χ2/df = 1.44, IFI = .98, TLI = .97, CFI = .98, SRMSR = .05, RMSEA = .04) are presented in Fig. 7. Comparing Figs. 4 and 7, our formative model was superior to the reflective model (Δχ2 = 53.64, Δdf = 11, ΔCFI = .03, ΔRMSEA = .01). The negative direct path revealed that temptation (low cognitive impairment and high self-control) was significantly related to unethical intentions (−.22, p < .001), supporting Hypothesis 1. Our significant, positive indirect path suggested that a high level of temptation (high cognitive impairment and lack of self-control) was related to poor MI (low stewardship, but high cognitive meaning of money) (.16, p < .05) that, in turn, was related to high unethical intentions (.28, p < .001) (Hypotheses 2 and 3). The overall impact from temptation to unethical intentions (−.170) was the sum of the direct impact (−.215) and the indirect impact (.045 = .16 * .28). Carefully controlled malicious temptation—low cognitive impairment and high self-control—was related to deviant intentions. Overall, temptation creates a dark impact on unethical intentions for participants in the whole sample. Among five sub-constructs, cognitive impairment (.59) and self-control (.40) contributed significantly and positively to temptation. Stewardship behavior (−.15) and cognitive meaning of money (.34) contributed significantly to MI. Regarding unethical intentions, corrupt intent (.89) seemed to be more prevalent than deception (.77) and theft (.63).
https://static-content.springer.com/image/art%3A10.1007%2Fs10551-012-1475-3/MediaObjects/10551_2012_1475_Fig7_HTML.gif
Fig. 7

Results of our theoretical model involving temptation (formative), MI, and unethical behavior intentions (the whole sample)

Males

Figure 8 (χ2 = 181.77, df = 148, p < .0308, χ2/df = 1.23, IFI = .98, TLI = .97, CFI = .98, SRMSR = .05, RMSEA = .03) shows that the direct path was negative (−.22, p < .01) (Hypothesis 1). For the indirect path, temptation was not significantly related to MI (.02) that, in turn, was significantly associated with unethical intentions (.22, p < .01), supporting Hypothesis 3, but not Hypothesis 2. MI was not a mediator. The overall indirect impact from temptation to unethical intentions was inconsequentially small (.004 = .02 * .22). Both MI and temptation contributed significantly to unethical intentions. The total impact from temptation to unethical intention was negative [total (−.215) = direct (−.219) + indirect (.004)]. Corrupt intent (.95) had the strongest factor loading, followed by deception (.76) and theft (.64). For males, temptation has a strong dark impact on unethical intentions. That is, our results also support the notion that cold-hearted executives in recent scandals strategically planned, cleverly organized, deceitfully misled, and carefully executed their unethical behaviors (theft, corruption, and deception) with concerted efforts and executive function. These unethical acts are not caused by cognitive impairment or lack of self control nor by accidents or honest mistakes. From a different perspective, individuals without the proper training at elite business schools and intellectual competencies probably do not have the mental capacities to execute these unethical behaviors.
https://static-content.springer.com/image/art%3A10.1007%2Fs10551-012-1475-3/MediaObjects/10551_2012_1475_Fig8_HTML.gif
Fig. 8

Results of our theoretical model involving temptation (formative), MI, and unethical behavior intentions (the male sample)

Females

The negative direct path was non-significant (−.171). For the positive indirect path, temptation was related to MI (.34, p < .01) that, in turn, was associated with unethical intentions (.48, p < .01) (Fig. 9). Results supported Hypotheses 2, 3, and 4, but not Hypothesis 1. The indirect impact from temptation to unethical intentions was substantial (.166 = .345 * .480). The overall total impact from temptation to unethical intention was negative, but trivial [total (−.005) = direct (−.171) + indirect (.166)]. Deception (.90) had the strongest factor loading, followed by corrupt intent (.52) and theft (.40). For females, temptation has a weak dark impact on unethical intentions. We will not repeat the same MANOVA results here.
https://static-content.springer.com/image/art%3A10.1007%2Fs10551-012-1475-3/MediaObjects/10551_2012_1475_Fig9_HTML.gif
Fig. 9

Results of our theoretical model involving temptation (formative), MI, and unethical behavior intentions (the female sample)

Discussion

In this study, we investigate temptation from the perspectives of consumer behavior, the psychology of money, and business ethics. We explore the relationship between temptation and unethical behavior, treat MI as a mediator, and examine the direct and the indirect paths simultaneously using the whole sample and across gender based on multi-panel data collected from 340 part-time employees who are also university students in a business class. This study reveals several novel and counterintuitive insights. We briefly present our theoretical, empirical, and practical contributions below.

Theoretical Contributions

First, we carefully define the temptation construct using reflective and formative theoretical models and present solid empirical support for this individual difference variable. We adopt an alternative model with facet constructs and multiple reflective measures (see Fig. 6, Edwards 2011) that “avoids” the shortcomings of formative measurement. Our temptation construct is a label for its dimensions, considered collectively. The reflective temptation model has five strong factor loadings for its sub-constructs and a high Cronbach’s α (.81). For the formative model, the correlations among five constructs are all below .80, suggesting that all sub-constructs make significant and separate contributions to the overall temptation construct. Three constructs contribute positively, while two constructs contribute negatively to temptation. It has a good composite reliability (.81) (Table 1).

Second, we develop a theoretical model, solve a part of the mystery, and identify multiple faces of temptation—a negative direct path as well as a positive indirect path for the whole sample. Both the reflective and formative models provide similar results and a strong validity for the temptation construct. Specifically, our formative model identifies specific sub-constructs that make significant contributions to temptation and our SEM model: For the positive indirect path, people fall into temptation—lack of self-control and cognitive impairment—and display poor MI (poor stewardship behavior, but high meaning) that, in turn, entices them to have high unethical intentions. For the negative direct path, temptation—strong self-control and low cognitive impairment—is related to unethical intentions. That is, our results also support the notion that cold-hearted executives in recent scandals strategically planned, cleverly organized, deceitfully misled, and carefully executed their unethical behaviors (theft, corruption, and deception) with concerted efforts and executive function. These unethical acts are not caused by cognitive impairment or lack of self control nor by accidents or honest mistakes. From a different perspective, individuals without the proper training at elite business schools and intellectual competencies probably do not have the mental capacities to execute these unethical behaviors.

Temptation prompts cognition to support self-control in a “cold” non-visceral state, but prompts the same cognitive processes to support impulsive behavior in a “hot” visceral state (Nordgren and Chou 2011). Both “cold” and “hot” states reflect our direct and indirect paths of our theoretical model, respectively. Since the indirect path is positive, whereas the direct path is negative, a suppression effect exists (Shrout and Bolder 2001). Because the overall impact is negative and substantial, controlled temptation leads to unethical intentions.

Third, our multi-group analysis across gender reveals the following profound findings based on both reflective and formative models: a negative direct path for males and a positive indirect path for females. For males, their negative direct path creates a strong overall dark impact on unethical intentions due to (1) a powerful negative path and (2) a limited positive suppression effect. On the other hand, for females, their positive indirect path creates a negligible overall dark impact on unethical intentions because the strong positive suppression effect eliminates almost all the negative direct effect. Males display the “cold” state, whereas the females pay attention to the “hot” state. For males, their unethical intentions are dominated by “corruption,” whereas for females, by “deception.” The multiple faces of temptation reveal the following specifically: There is an important implication regarding business ethics for men and consumer behavior for women. Overall, males are more unethical than females among business students.

For our formative SEM model, only two sub-constructs—cognitive impairment and lack of self-control—contribute significantly to temptation. Low stewardship behavior and high cognitive meaning formulate the MI construct that is related to high unethical intentions. Stewardship of money makes significant contributions toward and formulates MI. The formation and consequence of a formative construct depend on the context of the study and offer additional information and insights when compared to a reflective model. Cognitive and control components of temptation (TPB, Ajzen 1991) help us understand this construct. Our findings provide important theoretical implications for researchers interested in studying consumer behavior (Baumeister 2002; Baumeister et al. 2008), the psychology of money (Milkovich et al. 2010), and deviant behavior (Kish-Gephart et al. 2010).

Empirical Contributions

Our very well developed theoretical constructs match with systematically applied and highly cited measures in the literature and a sample of business students with proper work experiences. We cannot provide counterintuitive, interesting, and novel discoveries without collecting data from a good sample. We demonstrate temptation’s strong reliability (Cronbach’s α and composite reliability), validity, and rigorous measurement invariance results across genders. Results enhance the generalizability of our findings and provide confidence to future researchers in conducting cross-cultural research in under-researched areas of the world.

Practical and Actionable Implications

Very little research has combined the fields of consumer behavior, the psychology of money (MI), and business ethics to investigate the temptation to unethical intentions relationships. When constructs—that do not normally come near one another—collide, the ultimate novelty of the solution will be greater (Amabile 1998; Tang 2010). We apply multiple lenses and provide a new, cross-disciplinary perspective by infusing the theory of free will—constructs traditionally dominated by scholars in the economic psychology and consumer behavior—into the business ethics domain.

We clearly demonstrate the complexity of identifying both positive and negative paths for the whole sample and across gender using a very simple, yet elegant and sophisticated theoretical model. We apply the carefully developed theory with solid psychometric properties to assess intrapersonal and interpersonal and future cross-cultural differences in temptation. Future researchers may develop training programs to help people assess and understand (cognitive and control aspects) temptation, money smart, unethical intentions, and other new constructs, propose possible changes to improve actionable behaviors, and enhance satisfaction in different aspects of their lives.

The self-control and cognitive thinking aspects of our temptation construct serve as a double-edged sword because strong self-control and cognitive ability are associated with unethical intentions, but a lack of self-control and cognitive impairment is related to poor MI. First, acts of self-regulation without rest or replenishment (Muraven and Baumeister 2000) impair subsequent self-regulatory efforts (Baumeister 2002; Gino et al. 2011). Self-control is the poorest among people who have performed a prior act of self-control.4 Sleep deprivation causes workplace deviance due to the depletion of self-regulatory resources (Christian and Ellis 2011). When crucial resources have been depleted, they are more likely to yield to temptation and act impulsively. People without a “strong will” become weak physically, psychologically, and spiritually. Second, recent scandals are not caused by executives’ lack of “intelligence” or “brains,” nor are they accidents, honest mistakes, or cognitive impairment, but are rather caused by their lack of “wisdom,” “virtue” (Feiner 2004, p. 85; Tang and Liu 2012) and by malicious intent. Most coldhearted executives and individuals with self control (will do) and executive function (can do) seize the opportunity to engage in unethical behaviors for financial gains. Alternatively, mentally challenged individuals probably cannot execute unethical intentions properly.

Since unethical intention is a small part of evil, our results help us understand the deeper meaning of The Lord's Prayer (also called the Pater Noster or Our Father), a central prayer in Christianity: “And lead us not into temptation, but deliver us from evil” (Matthew 6:13). In the process of performing miracles, Jesus said, “Take away the stone” (John 11: 39). In order to heal a deaf man who had a speech impediment; "He took him off by himself away from the crowd" (Mark 7: 33). These lead to one actionable implication for all of us. In order to deliver us from evil, we must remove all barriers of a secular environment polluted with materialism and selfish desires to a sacred milieu—to love one another (Sappenfield 2012). Religion may be one of the last resorts for teaching business ethics and promoting ethical decision making (Chen and Tang 2012). It is “natural” to tell the truth and “unnatural” to tell a lie (Heney 2012). Educators, managers, and average citizens may simply adopt the following four ways to start this grand challenge by (1) praying a little more to develop a deep conversation with our God—eight minutes in the morning and eight minutes in the evening, per day, (2) studying the faith and reading the Bible more—five pages a day, (3) giving a little more of ourselves and donating generously—one or two percent more than before to the church or charity, and (4) sharing the truth a little more and becoming an evangelist—to one more person a day than before (Sappenfield 2012). The first two deal with “love your God” and the latter two “love your neighbor”. This is to “love one another” or “love your enemies” (Chen and Tang 2012). Reciting the Ten Commandments and/or starting a new day with a prayer in the morning or in a business meeting may have the potential to set an ethical tenor for the event/day, enhance corporate ethical cultures, and reduce managers’ unethical behavior intentions in organizations. A sea change of the ethical social norm in schools, organizations, and society, or ethical community-building, is needed to fight against unethical behaviors.

The positive indirect path exists for females, but not for males.5 Here are some possible implications for consumers. Americans are on a diet. The prevalence of dieting varied by gender and race (the highest: white women, 21 % vs. the lowest: Hispanic men, 8 %). About 71 % of all dieters reported that they were dieting to improve health, and 50 % reported that they were dieting to lose weight (Paeratakul et al. 2002). Females are more likely to fall into temptation than males because those who want to control themselves (e.g., on diet) may deplete self-regulatory resources quickly, spend their money spontaneously when given an opportunity, engage in poor stewardship of money, and enjoy the moment (Baumeister et al. 1994, 2008; Tice et al. 2001). Anecdotal evidence suggests that males tend to exercise strong control, go directly to the store, and buy exactly what they want to buy quickly, whereas females are more likely to fall into temptation, lose their control, get distracted by advertisements and items on sale, make unnecessary purchases, and buy items that are not originally intended. Consumers’ purchasing behaviors are directly associated with their personal values (materialism and the love of money), financial responsibilities, demographic variables, previous acts of control, and various temptations in the social environment (Gardarsdottir and Dittmar 2012). Due to temptation, people become disoriented and lose their abilities to concentrate on important, long-term goals. Cognitive impairment causes impulsive behaviors as a consequence. At the end of the day, hungry and exhausted consumers, for example, may buy many goods/products for instant gratification rather than their long-term goals. With strong and sufficient financial resources, consumers may enjoy their consumptions. Without it, they may be deep in debt. Researchers and practitioners must simplify options and choices for products and services; reduce complexity, overload, stress, and fatigue (sleep deprivation); avoid the depletion of self-regulatory resources; and provide positive temptation (moral values) to enhance proper consumption and ethical decision making in organizations.

Limitations

Our reflective (Fig. 2) and formative (Fig. 3) models of temptation show strong relationships between the five sub-constructs and the overall temptation construct. Further, we have provided good Cronbach’s α and composite reliability for the temptation construct. However, two sub-constructs of temptation have weak reliability measures. Thus, future researchers may want to enhance these sub-constructs. Further, we collected data with a reasonable sample size from one institution in the southeastern US. Scholars may want to test our theoretical models in other institutions, cultures, and countries to enhance the generalizability of the constructs examined in the present study.

Conclusion

We investigate the relationship between temptation and unethical intentions, treat MI as a mediator, and examine the direct and indirect paths simultaneously based on multiple-wave panel data collected from 340 part-time employees and university (business) students. The positive indirect path suggests that yielding to temptation—high cognitive impairment and lack of self-control—is related to poor MI (low stewardship behavior, but high cognitive meaning) that, in turn, is related to high unethical intentions. Our counterintuitive negative direct path reveals that controlling temptation (low cognitive impairment and high self-control) is significantly related to unethical intentions (theft, corruption, and deception). Due to the multiple faces of temptation—falling and not falling into temptation—the overall impact of temptation on unethical intentions is substantially dark. It implies that maliciously controlled temptation is related to deviant intentions. Subsequent multi-group analysis across gender reformulates the mystery of temptation: For males, the overall dark impact of temptation on unethical intentions is substantial and significant due to a negative direct path. For females, a significant positive indirect path shows a negligible overall dark impact on unethical intentions. Females do not have a maliciously controlled temptation to directly engage in unethical behaviors, but are likely to succumb to temptation, become less money smart, and have high unethical intentions. Overall, males are more unethical than their female counterparts. Both falling “and” not falling into temptation lead to unethical intentions; temptation’s impact, however, varies across gender. Our findings offer great implications for researchers in consumer behavior and business ethics. Our counterintuitive, novel, and original theoretical, empirical, and practical contributions may spark curiosity and add new vocabulary to the conversation regarding temptation, money attitudes, consumer psychology, and business ethics.

Footnotes
1

Watch and pray so that you will not fall into temptation. The spirit is willing, but the fresh is weak. (Matthew 26: 41).

 
2

For to the one who has, more will be given, and he will have an abundance, but from the one who has not, even what he has will be taken away (Matthew 13: 12).

 
3

We do not discuss students’ second 48-item temptation scale, completed about 10–12 weeks apart (Cronbach’s α = .85), in this paper.

 
4

Now the serpent was the most cunning of all the animals that the Lord God had made. The serpent asked the woman, “Did God really tell you not to eat from any of the trees in the garden?” The woman answered the serpent: “We may eat of the fruit of the trees in the garden; it is only about the fruit of the tree in the middle of the garden that God said, ‘You shall not eat it or even touch it, lest you die.’” But the serpent said to the woman: “You certainly will not die!” (Genesis 3: 1–4)

 
5

The man relied, “The woman who you put here with me—she gave me fruit from the tree, and so I ate it.” The Lord God then asked the woman, “Why did you do such a thing?” The woman answered, “The serpent tricked me into it, so I ate it.” (Genesis 3: 12–13).

 

Acknowledgments

The first author would like to thank Dean E. James Burton, Jennings A. Jones College of Business, at Middle Tennessee State University for providing a Summer Research Grant in 2012, Editor-in-Chief Alex Michalos and an anonymous reviewer for their suggestions, Late Fr. Wiatt A. Funk, Fr. Mark Sappenfield (St. Rose of Lima Catholic Church), and Fr. Dave Heney (St. Paschal Baylon Catholic Church, Thousand Oaks, CA) for their inspiration, and Jingqiu Chen, Albert Ming-Dar Wu, and John Lipinski for their comments, encouragement, and insight.

Copyright information

© Springer Science+Business Media B.V. 2012