Utilizing job resources: Qualitative evidence of the roles of job control and social support in problem solving

Abstract

In resource-based models of job design, job resources, such as control and social support, are thought to help workers to solve problems. Few studies have examined this assumption. We analyzed 80 qualitative diary entries (N=29) and interviews (N=37) concerned with the in-role requirements of medical technology designers in the UK for problem solving. Four themes linked to using the resources of job control and social support for problem solving emerged. These were: (1) eliciting social support to solve problems; (2) exercising job control to solve problems; (3) co-dependence between eliciting social support and exercising job control to solve problems; and (4) using job resources to regulate affect. The results were largely supportive of the assumptions underpinning resource-based models of job design. They also indicated that the explanatory power of resource-based models of job design may be enhanced by considering interdependencies between various factors: how different job resources are used, workers' motivation to use resources, workers' knowledge of how to use resources and the use of resources from across organizational boundaries. The study provides qualitative support for the assumption that social support and job control are used to cope with demands.     

A game mechanism for single machine sequencing with zero risk

A problem is studied in which several non-cooperating clients compete for earlier execution of their jobs in a processing sequence of a single service provider in order to minimize job completion time costs. The clients can move their jobs earlier in a given sequence. They are assumed not to take a risky decision that can decrease their utility function. A game mechanism is suggested such that each client has no incentive to claim false cost and a social criterion is addressed, which is the minimum total cost of all clients. Algorithmic aspects of this mechanism are analyzed such as relations between the values of game equilibria and the social optimum, the computational complexity of finding a game equilibrium and the values of the price of anarchy and the price of stability.     

Integrating Social Network Effects in the Share‐Of‐Choice Problem

Accounting for social network effects in marketing strategies has become an important issue. Taking a step back, we seek to incorporate and analyze social network effects on new product development and then propose a model to engineer product diffusion over a social network. We build upon the share‐of‐choice (SOC) problem, which is a strategic combinatorial optimization problem used commonly as one of the methods to analyze conjoint analysis data by marketers in order to identify a product with largest market share, and show how to incorporate social network effects in the SOC problem. We construct a genetic algorithm to solve this computationally challenging (NP‐Hard) problem and show that ignoring social network effects in the design phase results in a significantly lower market share for a product. In this setting, we introduce the secondary operational problem of determining the least expensive way of influencing individuals and strengthening product diffusion over a social network. This secondary problem is of independent interest, as it addresses contagion models and the issue of intervening in diffusion over a social network, which are of significant interest in marketing and epidemiological settings.     

整体环境和个体关联对群体性事件产生与演化的影响

对群体性事件产生与演化规律的研究已经成为社会管理的重要主题,而发展迅速的计算社会学方法为深入研究这一问题提供了新的途径。在已有研究的基础上,通过考察群体性事件的部分案例,可以发现个体对政府的信任程度、个体利益诉求渠道和社会普遍情绪这些内生性因素构成了群体性事件发生的整体环境要素,这些内生性因素的存在和组合达到一定水平,就构成了群体性事件发生的重要条件,而在这些宏观条件下,个体之间通过社会网络产生的关联和相互作用对群体事件的产生与演化也有重要影响。通过基于社会网络的计算社会学模型的模拟检验,本文对群体性事件的产生与演化进行了计算分析,讨论了整体环境和个体关联的各要素的作用,获得了部分内生性因素在其他条件既定时引发群体性事件的临界值。研究工作为进一步研究群体性事件的演化与形成机制提供了必要的模型基础。     

A neuroscience-based model of why and when CEO social values affect investments in corporate social responsibility

Why and when do CEOs invest in corporate social responsibility (CSR)? We theorize how CEOs' intrinsic motivations – their social values – and the incentivizing context interact to determine the utility they attach to generating collectively beneficial outcomes in decision-making, subsequently manifested in organizations' CSR investments. Based on a review of neuroscience evidence, indicating that social values are associated with distinct patterns of neural activation, we propose that these values are the compass by which CEOs navigate in complex decision environments. For CEOs with other-regarding values, generating collectively beneficial outcomes is part and parcel of their utility function. They are intrinsically motivated to invest in CSR, regardless of context. In contrast, CEOs with self-regarding values derive utility from generating collective benefits only when it is monetarily or socially incentivized. They are extrinsically motivated to invest in CSR when they stand to gain from it personally.     

The triangle <Emphasis Type="Italic">k</Emphasis>-club problem

Graph models have long been used in social network analysis and other social and natural sciences to render the analysis of complex systems easier. In applied studies, to understand the behaviour of social networks and the interactions that command that behaviour, it is often necessary to identify sets of elements which form cohesive groups, i.e., groups of actors that are strongly interrelated. The clique concept is a suitable representation for groups of actors that are all directly related pair-wise. However, many social relationships are established not only face-to-face but also through intermediaries, and the clique concept misses all the latter. To deal with these cases, it is necessary to adopt approaches that relax the clique concept. In this paper we introduce a new clique relaxation—the triangle k-club—and its associated maximization problem—the maximum triangle k-club problem. We propose integer programming formulations for the problem, stated in different variable spaces, and derive valid inequalities to strengthen their linear programming relaxations. Computational results on randomly generated and real-world graphs, with \(k=2\) and \(k=3\), are reported.     

The evolution of leadership: Leadership and followership as a solution to the problem of creating and executing successful coordination and cooperation enterprises

This paper proposes that leadership and followership are not just evolved solutions to the problem of coordinating what to do once a group exists. Rather, leadership and followership also solve the problem of creating a group in the first place. Creating a group is a problem of meta-coordination: coordinating with others about what to coordinate about. Of all possible bases for coordinating or cooperating, only a tiny fraction will be embraced by others, and smaller fraction still will be successfully implemented and executed. No one individual has enough information to solve this problem on one's own. Leadership and followership solve this problem by creating a social marketplace, in which leaders propose possible coordination and cooperation enterprises, and followers evaluate and choose among these offered possibilities. This marketplace—in which different individuals propose and evaluate different coordination and cooperation enterprises—solves the problem of meta-coordination by exposing possible enterprises to the broader social market, which serves as a selective or culling regime. Leadership and followership are evolved information-processing roles within this social marketplace. Consequently, understanding the evolutionary psychology of leadership and followership requires understanding the challenges and opportunities inherent in this market dynamic. The present paper analyzes the tasks that must be carried out to successfully navigate this dynamic. This task analysis predicts a number of novel information-processing functions for the roles of leadership and followership, and suggests that leadership and followership are a broader set of phenomena than currently conceptualized. This broadened conceptualization has a number of important implications for future research, and suggests that leadership and followership may have played a more central role in the evolution of human coordination and cooperation than has been appreciated.     

Finding disjoint paths on edge-colored graphs: more tractability results

The problem of finding the maximum number of vertex-disjoint uni-color paths in an edge-colored graph (called MaxCDP) has been recently introduced in literature, motivated by applications in social network analysis. In this paper we investigate how the complexity of the problem depends on graph parameters (namely the number of vertices to remove to make the graph a collection of disjoint paths and the size of the vertex cover of the graph), which makes sense since graphs in social networks are not random and have structure. The problem was known to be hard to approximate in polynomial time and not fixed-parameter tractable (FPT) for the natural parameter. Here, we show that it is still hard to approximate, even in FPT-time. Finally, we introduce a new variant of the problem, called MaxCDDP, whose goal is to find the maximum number of vertex-disjoint and color-disjoint uni-color paths. We extend some of the results of MaxCDP to this new variant, and we prove that unlike MaxCDP, MaxCDDP is already hard on graphs at distance two from disjoint paths.     

Approximation algorithms for two variants of correlation clustering problem

Correlation clustering problem is a clustering problem which has many applications such as protein interaction networks, cross-lingual link detection, communication networks, and social computing. In this paper, we introduce two variants of correlation clustering problem: correlation clustering problem on uncertain graphs and correlation clustering problem with non-uniform hard constrained cluster sizes. Both problems overcome part of the limitations of the existing variants of correlation clustering problem and have practical applications in the real world. We provide a constant approximation algorithm and two approximation algorithms for the former and the latter problem, respectively.

     

The Optimal Degree of Discretion in Monetary Policy

How much discretion should the monetary authority have in setting its policy? This question is analyzed in an economy with an agreed‐upon social welfare function that depends on the economy's randomly fluctuating state. The monetary authority has private information about that state. Well designed rules trade off society's desire to give the monetary authority discretion to react to its private information against society's need to prevent that authority from giving in to the temptation to stimulate the economy with unexpected inflation, the time inconsistency problem. Although this dynamic mechanism design problem seems complex, its solution is simple: legislate an inflation cap. The optimal degree of monetary policy discretion turns out to shrink as the severity of the time inconsistency problem increases relative to the importance of private information. In an economy with a severe time inconsistency problem and unimportant private information, the optimal degree of discretion is none.     

A NOTE ON “COMMON DUE WINDOW SCHEDULING”

Kramer and Lee recently addressed a common due window scheduling problem with earliness and tardiness penalties, where earliness and tardiness penalty factors are constant and the common window size is given. They showed that the problem is polynomial when the location of the due window is a decision variable. For the case where the location of the due window is given, the problem is also polynomial when the latest due date is greater than or equal to the makespan, and they proposed a pseudopolynomial dynamic programming algorithm to find an optimal schedule when the latest due date is less than the makespan. In this note we address the problem for the case where the location of the due window is given. Specifically, we show that the problem is polynomial if the window location is unrestricted, and present a more efficient dynamic program algorithm to optimally solve the problem if the window location is restricted. The concepts of unrestricted and restricted window locations are defined in this note.     

Strategic planning and research and development—Can we integrate them?

The main problem affecting the R & D function has always been caused by its lack of integration with the enterprise. Such a problem makes it difficult to pass from invention to innovation—that is, to turn the invention into processes and products to be exchanged on the market. The author points out the main social and organizational problems which prevent R & D from entering the ‘circulatory system’ of the enterprise. The identification of such problems is important in order to set up and to implement innovative strategies. This is the first of two articles by Professor Petroni on this subject. The second article will appear in April 1983.     

The complexity of influence maximization problem in the deterministic linear threshold model

The influence maximization is an important problem in the field of social network. Informally it is to select few people to be activated in a social network such that their aggregated influence can make as many as possible people active. Kempe et al. gave a $(1-{1 \over e})$ -approximation algorithm for this problem in the linear threshold model and the independent cascade model. In addition, Chen et al. proved that the exact computation of the influence given a seed set is #P-hard in the linear threshold model. Both of the two models are based on randomized propagation, however such information might be obtained by surveys and data mining techniques. This will make great difference on the complexity of the problem. In this note, we study the complexity of the influence maximization problem in deterministic linear threshold model. We show that in the deterministic linear threshold model, there is no n ^1??? -factor polynomial time approximation for the problem unless P=NP. We also show that the exact computation of the influence given a seed set can be solved in polynomial time.     

An exact algorithm for the maximum probabilistic clique problem

The maximum clique problem is a classical problem in combinatorial optimization that has a broad range of applications in graph-based data mining, social and biological network analysis and a variety of other fields. This article investigates the problem when the edges fail independently with known probabilities. This leads to the maximum probabilistic clique problem, which is to find a subset of vertices of maximum cardinality that forms a clique with probability at least \(\theta \in [0,1]\) , which is a user-specified probability threshold. We show that the probabilistic clique property is hereditary and extend a well-known exact combinatorial algorithm for the maximum clique problem to a sampling-free exact algorithm for the maximum probabilistic clique problem. The performance of the algorithm is benchmarked on a test-bed of DIMACS clique instances and on a randomly generated test-bed.     

Leadership skills for a changing world: Solving complex social problems

Leadership has traditionally been seen as a distinctly interpersonal phenomenon demonstrated in the interactions between leaders and subordinates. The theory of leadership presented in this article proposes that effective leadership behavior fundamentally depends upon the leader's ability to solve the kinds of complex social problems that arise in organizations. The skills that make this type of complex social problem solving possible are discussed. The differential characteristics and career experiences likely to influence the development of these skills also are considered along with the implications of these observations for leadership theory and for the career development of organizational leaders.     

Beratung im Kontext des Neuen Steuerungsmodells in der Kinder- und Jugendhilfe

The main elements of the ongoing reform of youth welfare in Germany “Neue Steuerung” (“New Regulation”) are the reconstruction of its administration, local networking and the transfer of economical criterions to the context of social work. Advisors and coaches, working in this field, are confronted with a problem, which is highly characterized by institutional dynamics of changes, and especially with the question of efficiency of social measures. We think, it is important that advisers, coaches an supervisors, who work in this field of “New Regulation”, are informed profoundly of the current state of the reform of the administration in their region, that they find their own point-of-view to the theme of pressure in financing social measures and social providing, and that they create a flexible supply of consultation, which is comprehensive in methods and that they cooperate with their clients` institutions.     

道冲突与企业间协作：第三方介入的调节作用

以社会平衡理论和营销渠道组织间关系的相关研究为基础，探讨渠道冲突对企业间协作的影响，并检验第三方介入对冲突与企业间协作之间关系的调节作用。收集550份有效调查数据，应用统计方法分析数据和检验假设。结果发现：渠道冲突对制造商和经销商之间的协作有负向影响，会减少双方共同制定计划与共同解决问题的行为；而制造商邀请第三方介入进行调解，则有助于弱化渠道冲突对共同制定计划与共同解决问题的负向作用。另外，我们还发现，第三方介入还能够促进合作双方的共同制定计划与共同解决问题，进而对双方的渠道合作绩效有积极的影响。     

Supported,detached, or marginalized? The ambivalent role of social capital on stress at work

Relationships with work colleagues can mitigate job stress; this article proposes a new perspective on such effects, in accordance with social capital theory, to delineate the potentially distinct impacts of the two dimensions of relational and structural social capital. A partial least squares analysis of network data in a medium-sized company (N = 343) offers evidence of an effect of the relational dimension (tie strength), through social support. The structural dimension (bridging ties, i.e. whether an employee has social ties with members of other departments) reveals a dual effect involving reduced stress but also diminished social support, which can increase stress. These dual effects reflect the two levels on which bridging ties act, namely, cognitive (selfdistancing) and social (marginalization from the immediate work context) levels. Next, with two scenario-based experiments (N = 289 and 245), the authors manipulate bridging ties and gain further evidence of the proposed mechanisms. These findings highlight the social underpinnings of stress and the critical role of the structure, not just the quality, of work relationships. They also identify a dark side of bridging ties, which can enhance individual performance but also create the potential for negative wellbeing outcomes.     

需求响应下解决交叉补贴的阶梯电价方案研究——基于社会福利最大化视角

我国电价交叉补贴问题非常严重，其无论从经济效率还是公平上而言都是不合理的，必须尽快解决。通过对现行电价政策分析，阶梯电价政策可以解决交叉补贴问题，但现行方案效果不明显，因此需要调整。不仅如此，由于各档次用户对电价变化的需求响应程度存在差异，调整阶梯电价来解决交叉补贴的方案有许多，故存在一个社会福利最大化的解决方案。本文以社会福利最大化为目标，调整各档用户的电价，同时引入拉格朗日函数，设计出最优解决交叉补贴问题的阶梯电价方案，得到各档相应的电价比值。结果表明，当分档电价比值为1：1.62：2.41时社会福利存在极大值，此时阶梯电价方案是众多方案中的最优方案，社会福利全年增加约为702.00亿元。此方案在解决交叉补贴问题的基础上还兼顾了用户间公平和承受能力，对当前电价改革具有重要参考价值。     

P2P Marketplaces and Retailing in the Presence of Consumers' Valuation Uncertainty

Can peer‐to‐peer (P2P) marketplaces benefit traditional supply chains when consumers may experience valuation risk? P2P marketplaces can mitigate consumers' risk by allowing them to trade mismatched goods; yet, they also impose a threat to retailers and their suppliers as they compete over consumers. Further, do profit‐maximizing marketplaces always extract the entire consumer surplus from the online trades? Our two‐period model highlights the effects introduced by P2P marketplaces while accounting for the platform's pricing decisions. We prove that with low product unit cost, the P2P marketplace sets its transaction fee to the market clearing price, thereby extracting all of the seller surplus. In this range of product unit cost, the supply chain partners are worse off due to the emergence of a P2P marketplace. However, when the unit cost is high, the platform sets its transaction fee to be less than the market clearing price, intentionally leaving money on the table, as a mechanism to stimulate first period demand for new goods in expectation for some of them to be traded later, in the second period, via the marketplace. It is not until the surplus left with the sellers is sufficiently high that the supply chain partners manage to extract some of this surplus, ultimately making them better off due to a P2P marketplace. We further analyze the impact of a P2P marketplace on consumer surplus and social welfare. In addition, we consider model variants accounting for a frictionless platform and consumer strategic waiting.