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This paper seeks to identify the up‐stream supply chain member's (manufacturers, suppliers, supplier's service providers) characteristics, economics, dynamic capabilities, technology and institutional perspectives of risk in relationship to develop a trust building model through risk evaluation and to address the issue: should a supply chain member strive to build the trust or strive to reduce the risk with its members and from which perspectives?

A conceptual framework was developed considering five key perspectives (characteristics, economics, dynamic capabilities, technology and institutions) to evaluate the member's risk in relationship and derived the hypothesis from the framework. A survey was conducted in UAE packaged food industry upstream supply chain covering senior managers of 102 companies. Data were analysed using multiple regression analyses through SPSS. The selected supply chain members of this industry include packaged food products companies as manufacturers, packaging material converters as suppliers of packaging material to manufacturers and packaging raw material suppliers as supplier's suppliers of manufacturer.

From the survey results it is found that characteristic and institutional risk perspectives influence significantly to initiate a trustworthy relationship. Economics, dynamic capabilities and technology risk perspectives play a significant role to maintain trust in relationship. No perspective of members is found to be significantly risk‐free.

This study has identified the perspectives of risk that can initiate and build trust between supply chain members in the context of a global business environment with a strong institutional system. Further research is required to identify the supply chain member's risk‐worthy characteristics, threshold levels of risk bearing capacity and the extent to which the institutions can reduce the membership risk to build trust.

The study results suggest that the supply chain members should strive to reduce the membership risk levels to build trust rather than striving to build trust to reduce the risk. As long as a member's risk levels are within their bearable limits trust can be considered as a risk coping mechanism and when the risk levels exceed their bearable limits the subject of trust turns into risk management/security management.

This study may be one of the first to develop a trust building model through a risk evaluation process and also one of the first to study the trust in supply chain member's relationship in UAE. Findings from this research should prove useful to management researchers and practitioners.

The purpose of this research paper is to examine the role corporate and individual risk (from the point of view of the pricing manager) plays in developing pricing strategies.

Managerial professionals in two graduate business programs were used to assess riskiness associated with pricing strategies. Grounded in attribution theory, t‐tests were used to compare the different types of risk associated with the various pricing strategies.

The findings suggest that pricing managers will view risk from different perspectives (i.e. corporate and individual) and that this “point of view” should have an impact on the pricing strategies selected.

Research limitations include the use of graduate students in lieu of actual pricing managers. However, this research is a first step in examining the different perspectives of risk that may be taken by managers.

Pricing managers and organizations alike should be made aware of how a point‐of‐view perspective regarding risk can have a significant impact on selecting pricing strategies. The results of the study could provide guidance for corporations so that they can make sure pricing managers have the “correct” point of view regarding the riskiness of pricing strategies.

The research is the first to identify and examine the different risk perspectives. This provides value for academic research because it is the first in the area of risk regarding the different perspectives.

The purpose of this paper is to develop a context dependent, multi perspective multilevel trust measurement instrument to measure supply chain members' trust.

Since trust is a context dependent phenomenon and the level of trust between partners cannot be measured easily, a conceptual framework is developed to measure supply chain partners' trust from risk perspective (i.e. risk related to characteristics, rational and institutions/security) considering the relationship as “Risky”, “Risk‐worthy” and “Not risky” and translated them in terms of trust perspectives as “No trust”, “Trust worthy” and “Trust”.

Although the research on trust emphasizes to focus on a member's characteristics such as benevolence, integrity, ability, reliability, credibility, etc, decision to trust require multiple judgments therefore trust should be measured from various context dependent perspectives at multiple levels in relationship from trustor's perceptions and calculations. The key perspectives of trust in supply chain relationship are; characteristics trust, rational trust (cost and benefit, dynamic capabilities, technology) and institutional trust/security system. An important argument of this concept is that trust can only be dyadic.

Researchers on trust have repeatedly confirmed that trust is a multifaceted and context dependent concept. However the business context may not remain the same in the dynamic business environment, therefore this conceptual framework can be used as generalized trust measurement tool.

This paper has attempted to develop a simple and practical multi level trust measurement tool for the complex multi‐dimensional construct of supply chain partners' relationship trust.

This study may be one of the first to develop a multi level trust measurement concept from risk perspectives.

The purpose of this paper was to present the stages of the Brazilian startups' organizational life cycle (OLC), identifying and describing the main factors related to the entrepreneurial and organizational perspectives, as well as the factors related to external relationship agents and the associated risks at each OLC stage. In addition, the variables that comprised the three perspectives above were used for a descriptive reading of the evolutionary process from the perspective of intellectual capital during the stages.

The type of research used was quantitative with a descriptive character. For data collection, the authors have used the survey method and two complementary questionnaires were used as research tools. The measurement scale used in these instruments was the 11-point Likert scale. In total, 100 Brazilian startups registered in the STARTUPBASE and residents in São Paulo comprised the sample of this research. For the data processing, it was used the exploratory factor analysis techniques, to identify the analysis factors, and the cluster analysis, to identify the OLC stages.

Based on the results obtained, four stages were identified and described to build the OLC model of this research: Stage I – conception and development; Stage II – organization and traction; Stage III – growth and scale; and Stage IV – consolidation and transition. In addition, the authors described the main lines of evidence found at each stage.

This research contributes to academic studies of the OLC in startups and the evolution of risks that originate from the relationship between external agents in the business environment and startups. Thus, a management map is built, which helps entrepreneurs and managers construct these businesses since such a management map allows identifying the risks and challenges that a startup needs to overcome to grow and develop.

The originality of this research lies in the adaptation of the OLC approach, which is widely used in studies analyzing the growth and development of mature organizations. The authors used this adaptation to analyze the growth and development of startups in Brazil. In addition, the identification and analysis of external agents that make up the business environment, as well as the analysis of the risks, originated from the relationships between the startup and these agents, brought original and essential results and discussions, both for OLC studies and for risk analysis studies in startups.

This study aims to explore and analyzes the risk factors in container shipping and logistics services using a dual perspective. The authors gather data not only from logistics service companies but also from their most important customers.

In this research, the authors used case study methodology (interviews and surveys) to examine risk factors that are related to one another within the interaction between logistics service companies and their customers in the emerging markets of the Mediterranean region (Turkey, Algeria, Tunisia and Libya).

The findings show the most important risk factors and compare them using a dual perspective. Customers identify additional risks and estimate their consequences as wider. Interestingly, oil price change plays a dual role because a price increase could be beneficial to the region; at the same time, however, the competitiveness of shipping would decrease. In both response groups, risk likelihood and risk consequence have a positive and statistically significant correlation.

The findings of the study are limited to one shipping/logistics service company. On a global scale, the company is medium-sized; however, in terms of Northern Europe, it is an important player. Extending its service portfolio to the Mediterranean region is an important step.

In emerging markets, risks go hand in hand with profitability, and companies need to apply extensive risk analysis and mitigation strategies to survive.

The southern Mediterranean region is showing some signs of economy recovery. Efficient, robust supply chains are in demand to support sustainable growth.

Using a case study approach in supply chain risk management in shipping is rather rare; this work is ground-breaking in that it uses dual perspective in the analysis.

The purpose of this paper is to investigate changes in the commercial real estate market dynamics as a function of and conditional to the shifts in market state-space environment that can influence agent responses.

The analytical design uses a comparative computational experiment to address the performance of property assets in the current market based on comparison with prior structural patterns. The latent variables developed across market sectors are used to test agent behavior contingent on the perspectives of capital asset pricing conditionals (CAPM) and a behavioral momentum/herd construct. The state-space momentum analysis can assist the comparative analysis of current levels and shifts in property asset performance given the issues that have arisen with the financial crisis of 2007-2009.

An analytic approach is employed framed by a situation-dependent model. This frame considers risk profiles characterizing the perspectives and preferences guiding a delineated market state. This perspective is concerned with the possibility of shifts in market momentum and representativeness conditioning investor expectations. It is observed that the current market (post-crisis) has changed significantly from the prior operations (despite the diversity observed in prior market states). The dynamics of initial findings required an additional test anchored to the performance of the general capital market and the real economy across time. This context supports the use of a modified CAPM model allowing the consideration of opportunity cost in a space-time dynamic anchored with the consideration of equity, debt, riskless asset and liquidity options as they varied for the representative agents operating per market state.

This paper integrates neoclassical and behavioral economic constructs. Combines asset pricing with prospect theory and allows the calculation of endogenous time-preferences, risk attitudes and formulation and testing of hyperbolic discounting functions.

The research shows that market structure and agent behavior since the financial crisis has changed from the investment and valuation perspectives operating as observed and measured from 1970 up to 2007. In contradiction to the long-term findings of Reinhart and Rogoff (2008), but in compliance with common perspectives and decision heuristics often employed by investors, this time things have changed! Discounting and expected rates of return are dynamic and are hyperbolic and not constant. Returns and investment for property assets are situational (market state-space specific) and offer a distinct asset class, not appropriately estimated by many of the traditional financial models.

Assist in supporting insights to measure in errors and equations that result in inefficient resource allocation and beta discounting that supports the financial crisis created by assets subject to long-term decision needs (delta function).

The paper offers a combination and comparison of neoclassic asset pricing using a modified CAPM (two-pass) approach within the structural frame of Kahneman and Tversky’s (1979) prospect theory. This technique allows the consideration of the effects of present bias, beta-delta functions and the operation of the Allais Paradox in market states that are characterized by gains and losses and thus risk aversion and risk seeking behavior. This ability for differentiation allows for the development of endogenous time-preferences and hyperbolic discounting factors characteristic of commercial property investment.

The purpose of this paper is to present a simulation‐based approach for modeling multi‐year non‐life insurance risk in internal risk models. Strategic management in an insurance company requires a multi‐year time horizon for economic decision making, for example, in the context of internal risk models. In the literature to date, only the ultimate perspective and, more recently, the one‐year perspective (for Solvency II purposes) are considered.

The authors present a way of defining and calculating multi‐year claims development results and extend the simulation‐based algorithm (“re‐reserving”) for quantifying one‐year non‐life insurance risk, presented in Ohlsson and Lauzeningks, to a multi‐year perspective.

The multi‐year algorithm is applied to the chain ladder reserving model framework of Mack (1993).

The usefulness of the new multi‐year horizon is illustrated in the context of internal risk models by means of a case study, where the multi‐year algorithm is applied to a claims development triangle based on Mack and on England and Verrall. This algorithm has been implemented in an excel tool, which is given as supplemented material.

To the best of the authors' knowledge, there are no model approaches or studies on insurance risk for projection periods of not just one, but several, new accident years; this requires a suitable extension of the classical Mack model; however, consideration of multiple years is crucial in the context of enterprise risk management.

Managers must make numerous strategic decisions in order to initiate and implement a business model innovation (BMI). This paper examines how managers perceive the management team interacts when making BMI decisions. The paper also investigates how group biases and board members’ risk willingness affect this process.

Empirical data were collected through 26 in-depth interviews with German managing directors from 13 companies in four industries (mobility, manufacturing, healthcare and energy) to explore three research questions: (1) What group effects are prevalent in BMI group decision-making? (2) What are the key characteristics of BMI group decisions? And (3) what are the potential relationships between BMI group decision-making and managers' risk willingness? A thematic analysis based on Gioia's guidelines was conducted to identify themes in the comprehensive dataset.

First, the results show four typical group biases in BMI group decisions: Groupthink, social influence, hidden profile and group polarization. Findings show that the hidden profile paradigm and groupthink theory are essential in the context of BMI decisions. Second, we developed a BMI decision matrix, including the following key characteristics of BMI group decision-making managerial cohesion, conflict readiness and information- and emotion-based decision behavior. Third, in contrast to previous literature, we found that individual risk aversion can improve the quality of BMI decisions.

This paper provides managers with an opportunity to become aware of group biases that may impede their strategic BMI decisions. Specifically, it points out that managers should consider the key cognitive constraints due to their interactions when making BMI decisions. This work also highlights the importance of risk-averse decision-makers on boards.

This qualitative study contributes to the literature on decision-making by revealing key cognitive group biases in strategic decision-making. This study also enriches the behavioral science research stream of the BMI literature by attributing a critical influence on the quality of BMI decisions to managers' group interactions. In addition, this article provides new perspectives on managers' risk aversion in strategic decision-making.

The purpose of this research is so that project managers can use a systemic approach to prioritizing the risks of outsourcing including an understanding of the external factors that could affect the prioritization.

A survey was designed by the authors and distributed to 2,500 outsourcing professionals from different organizations and the hypotheses were tested using the data from these surveys. The logic for forming the hypothesis is discussed for each hypothesis and so are the demographics of the respondents

External factors such as the type of technology involved, type of market targeted, location of outsourcing and the amount of experience the outsourcing professional had, did affect the prioritization of the outsourcing risks. Furthermore, trends were identified among the ranking of the outsourcing risks.

One of the constraining factors of this research, as in the majority of empirical research initiatives, was the limited sample size, which could potentially affect the rating. An increased sample size could have also provided the researchers with a more detailed insight into the interrelationships between the various outsourcing risks.

For the first time, the outsourcing risks have been prioritized using a systemic approach. The systemic approach has been used in the financial industry while analyzing risk but the authors have applied it to prioritization of outsourcing risks. This includes understanding the interrelationships between the risks and also the effect that external factors can have on the prioritization of those risks.

The aim of the research is to provide a method to evaluate supply chain risks that stand in the way of the supply chain objectives.

An analytical hierarchy process model is proposed to identify supply chain risk factors with a view to improving the objective of customer value. The two phases of the method are the prioritization of supply chain objectives; and the selection of risk indicators. A case study is also presented.

The appreciation of the most critical supply chain risks comes from careful evaluations of the impacts and a consideration of the cause‐effect relationships. The involvement of key managers is essential. In the case study the two most divergent evaluations were from the logistics manager and the sales manager.

Further application in various companies and industry sectors would be helpful to compare different cases and findings.

The model allows for flexibility in using (and the frequent monitoring of) a panel of indicators by management. The dashboard is composed of only a few indicators and helps in ensuring a synthesis among different perspectives. For these reasons it gives an useful contribution to practitioners.

The model seems helpful in creating awareness of supply chain risk. The involvement of managers from different areas is essential in establishing a thorough consideration of critical issues and interdependencies in determining a complete risk analysis. The method can support managers in setting up a priority hierarchy for risk treatment.