Analysis of Human Behavior in Organizations: Case of Blue Group.

• 

Analysis of Human Behavior in Organizations: Case of Blue Group.
Name of Student
Institutional Affiliation

Analysis of Human Behavior in Organizations: Case of Blue Group.
Human behavior in an organization immensely contributes to the overall performance of the company. For effective accomplishment of a company’s goals, it is prudent for the company’s employees to regularly meet and strategies on the best way to meet the set objectives. For the frequent organization of an organization’s meeting, integration of technology is ineluctable. Organizational behavior can be attributed to the study and use of acquired knowledge on how people act in a given organization. The key components of organizational behavior are the workforce, the structure, the technology implored and the external atmosphere that houses the organizational operations (Beer, 2017). In a bid for a workforce to join and work towards a common goal, the embodiment of a well-defined structure is ineluctable. Furthermore, different technological innovations have been adopted to see the successful completion of set objectives.
Characteristics of organizational behavior entail the following;

a) It presents a scientific approach to the relationship between cause and effect. This allows the formulation of problems within a framework of dependent and independent variables (Will & Mueller, 2019).
b) It encompasses a comprehensive and broad perspective. It allows analysis of behavior free from biasness (Schwartz, 2013).
c) It is oriented to change thus emphasizes the need for transition in human behavior as technology evolves throughout the sector.
d) It is shifting on performance based orientation.
e) Lastly it encompasses a distinctive humanist purpose which is detailed in its push for productivity, growth, development of oneself and focus on the quality of life (Beer, 2017).
Methodological Options for an Integrated Perspective
In considering the laws formulated in the ancient times concerning organization it is evident that the more an organization divides work in respect to skills the high it records the production results (Soltani et al., 2018). Consequently, an increased production is attributed to increased level of satisfaction at working level of an employee. Embodiment of bureaucracy in an industrial economy, is an efficient organizational adventure (Soltani et al., 2018). However, organization on peer state is also considered superior in an industrial economy. The error of the ancestors of organization theory was one of universalism. Their discoveries about the advantages of specialization, the relevance of workers’ preferences, and the coordination properties of hierarchy or peer groups were in good part valid, and, for those parts, were in fact resurrected in later models and are all still in use (Soltani et al., 2018). But the specification of the conditions under which those laws and properties are valid were at best very weak or absent in those classics. For quite a long time, and sometimes even now, then, what were hypotheses valid under different circumstances were treated as irreconcilable paradigms (Schwartz, 2013).
This error of universalism was denounced in organization studies, especially in the 1960s and 1970s, by what is known as ‘contingency theory’ of organization trying to specify what are the best forms of organizing given what types of technology are used, what tasks are performed, and what types of environmental uncertainties and interdependencies are faced (Schwartz, 2013). But this criticism was either not deep enough, or partially flawed, or not listened to enough, or all these things together, because the temptation to announce the discovery of unconditioned best ways of organizing keeps reappearing (Hofeditz et al., 2015). The criticism leveled at the possibility of formulating valid universal laws did not go far enough. Contingency theories ended by substituting the idea that “one best way of organizing” can be identified in general, with the idea that one best way of organizing can be identified in correspondence to each among a few different configurations of environmental and technological variables (Soltani et al., 2018). Bounded rationality theory provided the cognitive foundations for the development of a relatively autonomous organizational and behavioral science. However, it has ended by sharpening unnecessary divisions with its contrast between “absolute” and “bounded” rationality (Soltani et al., 2018).
There was also the acknowledgment of some more epistemic problems that echoed and in some cases anticipated other contributions on the nature of rationality in general and economic rationality in particular: the recognition of the intrinsic fallibility of human judgments and knowledge, of the models of the world that decision-makers are acting upon of the unavoidable imperfection in knowledge codification and transmission of the logical necessity of “decision premises” and “background knowledge” considered “out of discussion” providing a framework and a language for starting any decision process. These are sources of complexity and difficulties in knowing rather than in calculating. Subsequent perspectives have often paid attention only to partial aspects of bounded rationality (Hofeditz et al., 2015).
In many cases, important and possibly complementary perspectives on organization and economic behavior ‘do not talk’ to each other and generate incomparable predictions because they talk different languages: the descriptive language of how things are (descriptive laws), or the prescriptive language of how things should be if they are to produce certain consequences (prescriptive laws) (Schwartz, 2013). Some studies argue that they do not describe how decisions are made, they prescribe how they should be made in order to achieve superior results. However, it is always possible to reformulate prescriptive (and even normative) propositions – provided that they have an empirical basis – in descriptive propositions, in the form: if x is a necessary and/or sufficient cause of y, if one wishes to observe y, then it is necessary and/or sufficient to observe x (Schwartz, 2013). On the other hand, many regularities expressed in a descriptive language in organizational studies – such as “system size is correlated to decentralization” – are in fact valid only under some conditions of effectiveness (Beer, 2017). Hence they can be translated into prescriptive statements, such as “decentralize in large systems to improve performance.”
The lack of translation between descriptive and prescriptive models has merged with a controversy about the content of the “objectives” pursued by economic actors to generate another and possibly the most wrongly defined conflict among organizational perspectives – the contrast between “power” and “efficiency” explanations of organization (Will & Mueller, 2019). Efficiency is the generation of valuable outcomes through the use of the minimum possible amount of resources (Soltani et al., 2018). Encompassing the two components of benefits and costs, efficiency can be augmented not only by reducing costs, but also, and often more easily and productively, by creating more value. In practice this is quite important, as it may make the difference between, say, cutting personnel in order to be more efficient in one production or making an alliance to open a new line of production; or between accepting the first satisfactory partner for forming an alliance, for reducing search and negotiation costs, or investing more resources for finding a partnership that creates more surplus (Soltani et al., 2018). In fact, the value-increasing component of efficiency is commonly distinguished by the term effectiveness (capacity to reach valued outcomes).
In addition, efficiency is ill-defined unless the subjects bearing benefits and costs are defined and the time horizon is defined. Short- and long-term efficiency are almost proverbially conflicting criteria. When there are many subjects, efficient solutions are all those (and usually they are more than one) with respect to which no improvement for one or more party is possible without subtracting something from other parties (Pareto-efficiency) (Schwartz, 2013).
Furthermore, efficiency criteria can be applied in a static way (for example, in terms of comparative costs, it is more efficient to make rather than to buy a component) or in a dynamic way (for example, the marginal costs of adding one more item to internal production may be higher than the marginal costs of adding a procurement relation). Therefore, in the first place, different organizational solutions to the same problem can be explained by different efficiency criteria (Hofeditz et al., 2015).
Power is an even more multifaceted concept. As used in organization studies, it has been used in at least the following meanings, with quite different implications. Power has been used as a synonym for dominance: the reduction of the freedom of action and of the resources of other actors in order to make them dependent on one’s own will and redistribute resources to one’s own advantage (Schwartz, 2013). In this sense, a power criterion does make a difference with respect to efficiency and fairness criteria. Supposing that there is no incentive to impose a solution that can be improved both for oneself and for others, still one party (typically because it is much less substitutable than others) may be able to impose an arrangement in which it captures all the surplus created by cooperation or exchange and gives others their minimum acceptable reward rather than their fair share. Lastly, part of the confusion on the issue of power and efficiency stems from a lack of perception of the difference between the motives leading to an action (its “teleological explanation”) and the properties that this action has (its “functionalist explanation”) (Hofeditz et al., 2015).
The issue of natural selection has recently received increasing attention in organization
studies not only because of the growing influence of economic models in the field, but also because of the development of an influential research program in organizational sociology applying the concepts and tools of biological. In their first proposal of the new approach, studies have insightfully and understandably contrasted a change process based on natural selection with one based on learning, arguing that organization studies overrated the importance of the latter and neglected the former. In the first case “it is the environment which optimizes” (the firm chooses an organization form and the environment “chooses” a state which may be favorable or not), while in the second case individual firms change their internal structure to adapt to a changing environment (Soltani et al., 2018). Initially, then, this was a methodological distinction between processes of variation and selection of organizational solutions occurring at different levels – within a single actor (a firm in the case) through competition among alternative solutions, or among actors through competition among subjects “incorporating” different solutions (Schwartz, 2013). This was the origin of the hypothesis of “structural inertia” at the level of individual subjects: in order to see the effects of natural selection, let us “assume” that organization structures and behaviors, once adopted, cannot be further adapted by an actor but are exposed to competition with other choices.
In subsequent developments and debates, however, these “assumptions,” that were
and should have remained methodological conventions for isolating the effects of natural selection from those of learning, became interpreted as substantive predictions about whether organizational structures and behaviors are in fact inert or not, as assumptions on the “nature” of organization in this respect, thereby causing another mistitled division in organization studies. In fact, not only do both individual learning and natural selection processes obviously exist in reality, but, more importantly, they interplay rather than being mutually exclusive, so that one cannot be well understood without the other in social systems (Sarmoen et al., 2019).
Natural selection needs variation in structures and behaviors, but is fairly indifferent toward the origins of these organizational variations (inertia, random trials, intelligent adaptation, etc.) (Sarmoen et al., 2019) Furthermore, if economic actors, firms in particular, were permanently marked by an organizational “blueprint” from their birth to their death (like biological individuals), the rate of change and evolution would be as slow as in the evolution of natural species. Such a strict biological analogy would lead one to underestimate the rate of change and the importance and effect of natural selection itself on social constructs. In fact, conversely, competition and the possibility of natural selection are fundamental incentives for learning and adaptation, precisely because they are a “credible threat” but not a certain sanction (Hofeditz et al., 2015).
Adam Smith long ago and vividly described the advantages of the division of labor among different actors, or their specialization. The phenomenon documented by Smith is that of the spectacular increase in productivity that one can obtain through the specialization of workers in more and more focused activities to the point where they are no longer technically divisible (Schwartz, 2013). The great motor of economies of specialization is learning by deepening competence. The focus on an activity based on a single technique and its repetition trains the worker to perform that technique better. One discovers all the “tricks of the trade” building a repertoire of effective and efficient work procedures that permit one to solve production problems in order to obtain the best results in the shortest time without spending further time on analysis and decision-making. But there is more. The processes of discovery and growth of knowledge are never limited. To that extent, learning may sustain technical improvement and economies of experience over time indefinitely.
The complexity of the competences required in the activities reinforce this effect. The more difficult activities are, the longer the learning cycle required to master them, the greater the importance of specialization and experience. Where activities are very difficult, it is unlikely that a single person, a group of people, or even a firm, who succeed in mastering that set will be capable of performing equally well in another set of activities. A high division of labor and specialization, therefore, does not necessarily imply the “deskilling” and job-impoverishment with which it has been associated in the so-called “Fordist” or “Taylorist” applications of specialization in mass production industries. Highly specialized and professionalized forms of organization of work are common in modern economies (Beer, 2017).
The economies generated by the division of labor do not derive exclusively from the process of learning relevant techniques, but also from the learning and the development of cultural traits, cognitive, and emotional orientations that sustain performance in that activity (Hofeditz et al., 2015). For example, in a firm, the division of labor between those who produce and those who sell is not only a function of the technical differences that characterize the two types of activity. The production activities usually require and generate an allocation of attention, interest, and even a passion for the details, for the data, for ingenious and optimal solutions. Production activities also require and generate an orientation to short-term results and an adverse attitude toward risk. In contrast, sales activities usually require and generate strong orientation toward people and relationships, tolerance and acceptance of different mentalities and a plurality of solutions, an orientation toward medium-term results, less risk-averse attitudes and the capacity to confront and manage uncertainty. These specialized orientations are efficient in the performance of different work activities, and once formed in a particular person, they can produce diseconomies of variety. Although a variety of different techniques can be learned by one individual, it is increasingly difficult for one individual to acquire more than one mentality.
Economies of specialization are not generated exclusively from the division of labor and the focus on a technique by human resources, but also thanks to the specialization of technological resources. Machines, as well as humans, can be specialized. We need only think of the productivity gains caused by the change from universal tools (such as the hammer) to machines dedicated to a particular class of operations (such as the lathe), and then to machines specialized for only one type of transformation process and one output (such as an automatic assembly line) (Sarmoen et al., 2019).
For both human and technical resources, the great limit to specialization is the lack of flexibility, i.e. the inability to adapt to changing needs and demand. Flexibility implies, in fact, the opposite of specialization: generalism, the redundancy of competence with respect to the activity currently being performed, and the polyvalence of resources. A specialized economic actor is an actor exposed to risk; he “bets” on an activity and invest in resources that limit his capacity to become reconverted. He or she will win the bet only if the state of the future world remains favourable to the activities that can be performed with those resources – that is, if other actors demand those activities. As a consequence, even if there are economies of specialization in an activity, the opportunity to realize them and the incentives for actors to specialize in them depend also on other factors, such as the uncertainty of the demand for that type of activity. The advantages of specialization will be actually captured only if we can see a stable demand for that type of activity, or at least a demand that is cyclically and frequently favourable (Schwartz, 2013). Finally, the mere presence of economies of specialization should not automatically lead one to adopt an organization form based on a massive division of labor, for another reason too – the effect of other key variables on the degree of and type of division of labor that is effective and efficient, among which are the interdependences among activities (which is often the most important rival variable). The more activities are specialized and the more they are interdependent, the more they need to be coordinated.
Rationality can assume different configurations that, in economic behavior, materialize in different decision processes or strategies. These decision strategies are formulated here in a way conducive to comparative evaluation according to three criteria:
• to what extent are they able to link actions – and the results those actions are expected to produce – to the preferences and objectives of decision-makers (effectiveness)
• to what extent do they economize on the scarce resource of cognitive capacity and effort (efficiency)
• To what extent are they able to resolve conflicts between different actors with different objectives using that strategy (conflict resolution capacity) (Schwartz, 2013).
The main decision-making models that have been identified in economics, organization, and management can be described as particular, salient, and effective combinations or configurations of rules and procedures for defining and modifying the fundamental decision inputs: procedures for defining objectives, for generating and evaluating alternatives, and for learning from experience. In other words, one decision model or strategy differs from another if it is characterized by a different approach to any of these fundamental cognitive activities. The initial information conditions that make these diverse approaches or strategies applicable can be and will be specified (Schwartz, 2013).
A second type of motivation process can be retraced to the general characteristics of decision-making based on aspiration levels and acceptability judgments. Instead of taking into account utility functions to be maximized, actors can allocate effort and competence according to targets and goals to be reached. Hence, the informational requirements of this strategy of effort allocation are less ambitious than those of an expectancy based strategy. The core question about motivation then becomes: Are performance levels related to the type of goals actors formulate? Originally, March and Simon formulated this problem as one of “optimal tension”: low aspiration levels reduce search and lead to accepting low results; very high aspiration levels lead to lower success probability estimates, so that above certain levels action is inhibited (Schwartz, 2013).
Lastly, the process through which goals are set is obviously important and has been much studied. The results, however, are less obvious and clear than one might expect. The relationship between actors’ performance and their participation in goal-setting processes is very complicated. The ties connecting the specificity and the difficulty of the objectives with the performance described above are valid both when the actor autonomously sets personal objectives, and when the actor accepts objectives set by others (Soltani et al., 2018). Participation generates two contrasting effects: on the one hand, self-set objectives may not be as high as those which, in equal circumstances, would be set by others (a self-serving bias); on the other hand, the self-determination may solicit stronger conviction and dedication to goals (commitment) (Schwartz, 2013). But it has also been demonstrated that high levels of commitment are also obtainable when the objectives assigned by others are convincingly explained and understood and are connected to interesting rewards, and regular feedback is provided on the progress of the performance toward the objective (Beer, 2017). Participation is fundamental, however, when the performers themselves possess the relevant knowledge for formulating valid and accurate hypotheses on attainable objectives – i.e. “participating in goal setting is necessary for cognitive reasons and not motivational ones”.
Reinforcement theory, as applied to motivation, maintains that when consequences are attributed to one’s own actions and are perceived as positive, the probability that those actions will be repeated increases; whereas the perception of negative consequences of one’s own actions diminishes this probability. Reinforcements can be direct (rewards or punishments connected to actions) or indirect (abstention or absence of rewards and punishments).
Hence, the model considers four typical situations, called positive reinforcement, negative reinforcement, punishment, and extinction. Applying reinforcement theory to motivation has contributed notably to explaining apparently irrational behavior and developing
“positive-reinforcement programs” oriented toward correcting such behaviors and improving the relational climate. In fact, one of the characteristics of reinforcement processes is that of regulating (often inadvertently) behaviors that are given little explicit attention and analysis, such as those requiring quick interactions: interpersonal relationships, aspects of work that have not (yet) been analyzed because they have never constituted a problem, and habitual actions. The fact that these processes take place automatically does not, however, mean that they have consequences of little significance, whether in terms of the quality of inter- personal relationships, or in terms of direct impact on economic results (Soltani et al., 2018).
Adoption of virtual team is a new trend that is emerging owing to the current looming pandemic of coronavirus. In business organization, most trends are scrutinized before their implementation to assess the reliability and the consistence in service delivery.
Advantages of Virtual team integration
One of the advantages of virtual team integration is the ability to save on cost. The embodiment of this technology allows businesses to save on cost and huge expenses such as rental office, utility bills, and executive travels. Most of the big companies outsource their operations to the low cost places. Thus decreasing the cost of production with less cost on raw materials, operational charges and reduced wages for the employees in the set geographical regions (Sarmoen et al., 2019).
Virtual teams also foster the leveraging of the worldwide talent. The organization uses this technology to sources for talents beyond their geographical jurisdiction. This allows the organization to amalgamate expertise and specialists that can complete a project effectively. Furthermore, it increases the sharing of ideas and innovations among the organization’s human capital, thus increasing knowledge base (Will & Mueller, 2019).
There is increase in profit as a result of high productivity. Virtual team experts usually prioritize the task that is at hand. It is the primary function of the virtual team to uphold the structure of the organization. The members do not engage in time consuming bureaucratic processes of decision making which enhances the profitability.
Reduced time to market.
Most virtual teams have members from different time zones. This means that different members can work on the same project for the whole twenty four hours. This results in shortened time of product development while increasing response time to the demands in both local and worldwide markets.
Newer Opportunities
At the larger perspective of the technology. Virtual team has created new employment opportunities across the world. This is even commendable for the less mobile experts that are resistant to relocate and adapt to the new geographical demand or physical needs. Candidates can deliver results through this technology without the physical presence (Will & Mueller, 2019).
Disadvantages of virtual teams
Cost of the technology
An effective virtual team base is supported by softwares that necessitate instant sharing of video calls, emails. There is still no one communication software that can deliver the whole package holistically. This makes it expensive to install and maintain multiple softwares.
Conflicts, reduced collaboration and trust.
The differences in culture of the team members from different continents in the world predisposes the system to frequent conflicts. For example when American employee points at a situational incidence in the company, a counterpart from the any south Asian country will consider it as impolite and disrespectful. This results in conflicts, mistrust and affects collaboration resulting in reduced productivity and profits (Will & Mueller, 2019).
Social Isolation
Most of the effective virtual team players are adversely impacted by the lack of interaction at personal level. All communication in the virtual space are oriented to project being offered. In the normal job market, our co-partners in an organization form the bigger part of an employees’ social life, this is not the situation in the virtual systems. Thus, the team players in virtual systems may face stress and eventually depression (Sarmoen et al., 2019).
Virtual team system is prominent following the coronavirus pandemic. Most organizations are adopting improved leadership and management in a bid to realize the positive outcomes of virtual teams and overcoming the negativity it is associated with. Hence it is prudent for Blue Group organization to adopt better leadership and management strategies while embracing the use of virtual system.

References
Beer, M. (2017). Developing strategic human resource theory and making a difference: An action science perspective. Human Resource Management Review. https://doi.org/10.1016/j.hrmr.2017.11.005
Hofeditz, M., Nienaber, A., Dysvik, A., & Schewe, G. (2015). “Want to” Versus “Have to”: Intrinsic and Extrinsic Motivators as Predictors of Compliance Behavior Intention. Human Resource Management, 56(1), 25-49. https://doi.org/10.1002/hrm.21774
Sarmoen, N., Khalid, H., Abd Rasid, S., A L Baskaran, S., & Basiruddin, R. (2019). Understanding Human Behaviour in Information Security Policy Compliance in a Malaysian Local Authority Organization. Business Management and Strategy, 10(2), 64. https://doi.org/10.5296/bms.v10i2.14909
Schwartz, M. (2013). Developing and sustaining an ethical corporate culture: The core elements. Business Horizons, 56(1), 39-50. https://doi.org/10.1016/j.bushor.2012.09.002
Soltani, Z., Zareie, B., Milani, F., & Navimipour, N. (2018). The impact of the customer relationship management on the organization performance. The Journal of High Technology Management Research, 29(2), 237-246. https://doi.org/10.1016/j.hitech.2018.10.001
Will, M., & Mueller, J. (2019). Chapter 7 Change Management: The Organization as a Micro–Macro System. Management for Scientists, 99-111. https://doi.org/10.1108/978-1-78769-203-920191007