Pan-Pacific Conference XXXIV. Designing New Business Models in Developing Economies

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Violation, conceptually different to breach [8], is an “emotional and affective state that may … follow from the belief that one’s organization has failed to adequately maintain the psychological contract” [8, p. 230]. Breach, a rational and mental calculation [8], has a positive linear relationship to feelings of violation evidenced in a meta-analysis (r = .52) [4], as well as a segmented relationship [1]. The average observed effect size of violation predicted by breach examined with global measures of breach was significantly larger (r̅ = .47) compared to the composite measure (r̅ = .38) [4]. Intention to quit is a common response to a negative event [18]; thus, a negative event (breach), may increase an individual’s intent to leave. Breach has a positive linear relationship to turnover intention (r = .42) [4]. The average observed effect size using a global measure of breach (r̅ = .37) predicting turnover intention was not significantly different compared to the composite measure (r̅ = .31) [4]. A moderate relationship between breach and intention to quit (r̅ = .33), inclusive of both approaches in measuring breach, have also been reported [19]. A linear segmented positive relationship was also found between breach (using a composite measure) and turnover intention [1]. The following relationships, differently operationalized to Rigotti’s (2009) [1] study, are proposed: H1: Breach assessed with a global measure has a nonlinear relationship to (a) turnover intention, (b) violation, and (c) team altruism. H2: More variance is explained by threshold models in (a) turnover intention, (b) violation, and (c) team altruism compared curvilinear models. RESEARCH DESIGN Approach. A cross-sectional design with an online questionnaire was followed. Sampling and participants. The convenience sample consisted of 549 employees; the mean age was 36.3 years (SD = 9.34), tenure 7.61 years (SD = 7.85), and work experience 12.8 years (SD = 9.1). The sample consisted predominantly of males (56.5%), low-skilled workers (41.0%), and employees with upper secondary education levels (31.5%). Measuring instruments. Breach and violation were measured with Robinson and Morrison’s [20] scales. Turnover intention was measured using Roodt’s [21], [22] scale. Team altruism was measured with Van Wyk’s [23] scale with items rephrased to assess individuals’ altruistic behavior. Five-point Likert response scales were used for all items. Intercorrelations and reliabilities are reported in Table 1. TABLE 1: Intercorrelations and Cronbach’s alphas 1 2 3 4 1. Breach (.92) 2. Team −.43* (.95) altruism 3. Turnover int. .44* −.29 * (.76) 22 4. Violation .47* −.26 .40* (.90) * M 2.61 3.75 2.74 2.01 SD 1.17 0.78 1.01 1.19 n = 548–549. *p < .001. Reliabilities on the diagonal. The correlations between breach and violation (r = .47, p < .001) and turnover intention (r = .44, p < .001) were similar to previous studies, ranging between r = .52 [4] and r = .54 [1] for violation, as well as r = .33 [19] and r = .42 [4] for turnover intention. Analyses. A CFA revealed an acceptable fit to the data (Satorra-Bentler χ 2 (370) = 822.018, CFI = .950, SRMR = .052, RMSEA = .047, and RMSEA 90% CI: .043–.051; robust values are reported). Hierarchical regressions, with breach centered (mean) [1], [7], were used for linear- (Step 1) and quadratic models (Step 2). Initial parameters of the threshold models 2 were obtained from Step 1 of the hierarchical regressions; bb1 was set at −1. SPSS 23’s nonlinear regression function was used to estimate optimal parameter values and regression statistics [24]. Control variables were excluded similar to [1]. R 2 s were compared with partial F- tests. RESULTS Regression results (Table 2) evidenced that breach explained 18% (team altruism), 19% (turnover intention) and 22% (violation) variance in linear models (Step 1). All curvilinear relationships (Step 2), with small explained variances (between 0.2% and 0.4%), were insignificant, thus not explaining an improved fit to the data. Hypotheses 1 a-c are rejected. Parameter values and segmented regression results are reported in Table 3. The inclusion of a knot (threshold) for all variables led to an improved fit (i.e., increased R 2 ) to the data. The effect of breach on turnover intention is intriguing. Rigotti [1] and this study evidenced a positive relationship. However, in this study, a decrease in intensity in turnover intention (bb1 = −.196) followed after the threshold (knot = 2.684), compared to Rigotti’s [1] study where an increase in intensity (bb1 = .68) was observed following the threshold (knot = 2.84). The effects of breach on violation in these studies followed a similar pattern, except for an earlier threshold (knot = 1.917) revealed in this study. A comparison between linear and threshold models revealed an increase in explained variance (R 2 ) team altruism (18.2% to 18.7%), turnover intention (19.4% to 19.8%) and violation (21.6% to 22.5%); Rigotti (2009) [1] also reported more explained variance (R 2 ) in turnover intention (8% to 11%) and violation (24% to 36%). A comparison of the explained variance between discontinuous linear and threshold models are 2 Model specified: ba0 + ba1*breach + bb1*(breach−knot1)*(breach ≥ knot1)
eported in Table 4. Partial F-tests revealed that threshold models did not statistically better fit the data compared to linear models for team altruism, turnover intention, and violation. Only the threshold model for violation statistically better fit the data, with 0.9% additional explained variance (p < 0.05), compared to the quadratic regression. Only Hypothesis H2 b is accepted. Rigotti (2009) [1] presented similar results for turnover intention and violation. TABLE 2: Regression results (breach as independent variable) Team altruism Turnover intention Violation ß ΔR 2 ΔF ß ΔR 2 ΔF ß ΔR 2 ΔF Step 1 .182 121.932* .194 131.510* .216 150.369* Breach −.427* .441* .464* Step 2 .002 1.512 .004 2.903 .004 2.543 Breach 2 .051 −.070 .065 Adj. R 2 .182 .195 .216 F 61.779* 67.436* 76.668* n = 548–549 after listwise deletion. Standardized regression coefficients are reported. *p < .001. Control variables excluded. TABLE 3: Parameter estimates for segmented regression Dependent variables ba0 ba1 bb1 Knot 95% CI for knot SS R R 2 Team altruism 4.588 −.331 .206 3.667 2.304– 270.197 .187 4.551 Turnover intention 1.551 .491 −.196 2.648 1.221– 448.748 .198 4.075 Rigotti (2009) [1] 1.130 .100 .680 2.840 2.590– 255.980 .110 3.090 Violation 1.343 .104 .458 1.917 1.225– 598.812 .225 2.609 Rigotti (2009) [1] 1.390 .220 .850 2.640 2.460– 403.030 .250 2.820 n = 548–549 after listwise deletion. Control variables excluded. SS R = Sum of squares (residuals) TABLE 4: Comparisons between segmented regression, linear, and quadratic models with partial F-test Comparisons Segmented regression vs. linear regression Segmented regression vs. quadratic regression ∆F = (R 1 2 −R 2 2 )/(df 1 −df 2 ) [1]. *p < .050 (1−R 2 1 )/ n−df 1 −1 Turnover Team altruism intention Violation ΔR 2 .005 .004 .009 ΔF(df1, df2) 1.115 (3, 544) 0.903 (3, 543) 2.106 (3, 544) p .342 .440 .098 ΔR 2 .005 .003 .009 ΔF(df1, df2) 1.673 (2, 544) 1.016 (2, 543) 3.159 (2, 544) p .189 .363 .043* 23
Page 3: PAN-PACIFIC CONFERENCE XXXIV Design
Page 6 and 7: 2017 PAN-PACIFIC PROGRAM COMMITTEE
Page 8 and 9: The Pan-Pacific Business Associatio
Page 10 and 11: TUESDAY, MAY 30, 2017 13:30 - 15:00
Page 12 and 13: WEDNESDAY, MAY 31, 2017 13:30 - 15:
Page 14 and 15: The Adverse Effect of Psychological
Page 16 and 17: Sake Branding Strategy: Securing Ne
Page 18 and 19: The Failure of Transport Megaprojec
Page 20 and 21: WP12 International Finance Alpamayo
Page 22 and 23: INDEX Anderson, John WA12 Iluz, Mic
Page 24 and 25: xx
Page 27 and 28: Women Entrepreneurs and Family Firm
Page 29 and 30: catering for the local market. In o
Page 31 and 32: three groups with performance´ dif
Page 33 and 34: Cross-Disciplinary Education: Not B
Page 35 and 36: Attitudes Towards Servant Leadershi
Page 37 and 38: [6] Liden, R.C., Wayne, S.J., Zhao,
Page 39 and 40: (SD = 7.77), and work experience 12
Page 41 and 42: A representative emotion inventory
Page 43 and 44: emergence of a paradigm. In I. J. G
Page 45 and 46: OBJECTIVE The primary objective of
Page 47: Threshold effects of psychological
Page 51 and 52: The adverse effect of psychological
Page 53 and 54: pp. 283-289, 2011. [6] T. Vantilbor
Page 55 and 56: the scales are reported in brackets
Page 57 and 58: The Key Characteristics of Necessit
Page 59 and 60: At a glance, there appears to be so
Page 61 and 62: Job Calling, Work Identity and Job
Page 63 and 64: jobs to achieve set milestones that
Page 65 and 66: competency model is well founded on
Page 67 and 68: I-deal, I-craft, I-perform: A theor
Page 69 and 70: changes that affects their roles (G
Page 71 and 72: mechanisms.There were three overarc
Page 73 and 74: Table 1. Efficiency Results. DMU DE
Page 75 and 76: Not by Bread Alone: Estimating Futu
Page 77 and 78: squeeze more potatoes for direct hu
Page 79 and 80: well explains glocal with a holisti
Page 81 and 82: motor-vehicle industry in the Johan
Page 83 and 84: The Collaboration with Infrastructu
Page 85 and 86: Table1.Koshino Shu Kura (Jyoetsumyo
Page 87 and 88: product: its focus is on the needs
Page 89 and 90: The Rise of Populism in the West an
Page 91 and 92: It is important to note that althou
Page 93 and 94: 1.3 1.2 1.1 1 0.9 0.8 0.7 0.6 Commu
Page 95 and 96: 0.85 customs, the reduction in time
Page 97 and 98: Table 1. Confirmatory Factor Analys
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Uncovering the Beauty of the Capita
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the largest number of research stud
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An Exploratory Study regarding Mode
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According to the results of hierarc
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Standard Sake has been circulated b
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Can Ethics Be Used as a Tool of Inf
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85
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Defensive reactions as potential re
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Data gathering methods Data (in thi
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utility by comparing with the exist
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Virginia Tech - most calculations f
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Aggression and bullying attributes
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implications for both the individua
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The Role of Factory Facilities on S
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[44]. The following hypotheses are
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Delhi’s garment sector. In Toward
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A Manager’s personal value system
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commenting that good staff would le
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Law, Ethics and Business -How compa
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But to accept as quote, not reprodu
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integrity. In identifying the posit
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Consumer Awareness of Supply Chain
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Applications of Supplier Governance
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oth relational governance mechanism
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changing environment will disrupt g
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The Seven Efforts of Toyooka City:
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Study Related to Factors causing Fo
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- More people tend to choose privat
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students wishing to go to Italy. Ho
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investigating a multitude of design
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The failure of transport megaprojec
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C. Gautrain Gautrain is a high spee
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Delivering the required supply chai
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TABLE 1: Ranking of sills requireme
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[16] Taylor, M. B., 2016. A strateg
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divested fifty-nine percent of its
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Information Technology Project Fail
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Factors of IT project failure One o
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TFIDF w, a = TF w, a * IDF w (1) ID
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A Big Data Processing of Anxiety an
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Anxiety Index is defined as the rat
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serious problems due to pet fires,
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Deployment of Japanese Companies to
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stable politics and society situati
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APEC 61 437 615 21 634 2.8 World 11
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esults in higher levels of adaptati
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Web 2.0 tools for Virtual Reference
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Yes % 12.5% 14.8% 31.5% 33.2% 60.5%
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(Brundage, 2015), reminding one of
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CONCLUSION The review fostered a br
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significant causes of information o
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Circulation Type Farm Waste Managem
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IV. FUTURE CHALLENGES AND ANTIMICRO
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webpages, the Scopus database, Webo
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Supply Chain Materials Flow and the
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more speed, greatly exceeding the p
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To identify the external and intern
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Equality platforms. Also equity ref
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The Strategic Process in Large Ecua
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CONCLUSION AND DISCUSSION The resul
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12/10 12/11 12/12 13/01 13/02 13/03
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Business and Social Initiatives in
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case No. SKS-069. Boston: Harvard B
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Purchase intention Purchase intenti
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Signing the Annual Report of the Sw
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waste. A person without any powers
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2. DEVELOPMENT OF HYPOTHESIS Existi
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Perceptions of financial institutio
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Table1: Perceptions in business eti
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Roles of Regional Absorptive Capaci
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theoretically and intuitively sound
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still intriguing, (Carrington, 2013
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The effectiveness of strategic mana
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improved planning and a reduction i
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elatively stable collection of soci
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Measuring human capital disclosure
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DISCUSSION Managerial implications
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emain in the organization as they m
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Mega transport and logistics infras
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B.‘The Boston Big Dig’ - U.S.A.
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1 if St k ( k 1,2) Skt 0 otherwi
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India’s Technology Initiatives: I
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engine, sanitation, health and work
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Enterprise Finance, Agency), Develo
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Saharan African countries [8]. It i
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Systemic exclusion - barrier to eff
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ecause they focus on managing the r
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II. LITERATURE REVIEW The role of l
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60 50 40 30 20 10 0 Graph 3: Locati
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[25] Blok, M.M., Groenesteijn, L.,
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conducted in ways that diminishes t
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the supply chain. Second, suppliers
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In addition, firms’ responses to
Page 285 and 286:
Limitations of the Theory of Planne
Page 287:
[6] Barney, J. Firm resources and s
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Pan-Pacific Conference XXXIV. Designing New Business Models in Developing Economies

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