A HOLISTIC MODEL OF COGNITIVE THEORY TO EXPLAIN KNOWLEDGE CONSTRUCTION AND DISSEMINATION IN ORGANIZATIONS USED FOR COMPETITIVE ADVANTAGE

2.1. Knowledge-Based View of the Firm as a Starting Point for Organizational Learning

The knowledge-based view of the firm (Grant, 1996) that supports the discipline of organizational learning provides some substantive grounding for how organizations collectively learn. The definition provided by Grant (1996) that “knowledge is that which is known” (p. 110) is problematic, as acknowledged by the author, as a starting point for discriminating between what is processed information and what is valuable knowledge that the firm can use for dissemination to employees to be used for its competitive advantage. The definition does not explain how knowledge is created or distinguished from simple data or organized information. From a theory perspective, constructs must be distinguishable from one another to provide the explanatory power needed to adequately describe how a phenomenon works so that it can be appropriately modeled and tested, with its hypotheses opened to falsification (Popper, 1965; Rosenberg, 2015). For this article, the following definitions hold (Warren & Robinson, 2018):

• Data are unstructured, unprocessed bits of information.

• Information is processed, organized, and meaningful data.

• Knowledge is information analytically deemed to have either individual or group utility or application.

It is important to note that knowledge is not static and that all current, accepted knowledge must be regularly tested to ensure that it continues to have utility. While valued, tested knowledge can function as a resource for competitive advantage, developing this intellectual capital requires time investments by individual employees to uncover new information and cognitively process it to make it valuable to the firm. Further, the dissemination of any new knowledge and its use by others is limited by the firm’s ability to communicate it and the absorptive capacity of the individual employees, governed by their cognitive abilities. This situation limits knowledge sharing and acquisition in an organization.

2.2. Organizational Learning and the Knowledge-Based View

Organizational learning as a construct has existed both in theory development and as a research topic since at least the late 1980s, becoming a primary focus of business organizations with Senge’s (1990) publication that bridged learning and business concepts to improve performance. Unfortunately, much of Senge’s work is anecdotal, based on his observations, and needs the incorporation of learning theory explanations from the disciplines of education and psychology. There are no references in the works of Senge (1990), Nonaka (1994), Grant (1996), or those that followed that included critical business work in learning organizations or seminal educational research and theory pieces that explain or test how learning takes place at the individual level. Further, much of the work is grounded in behaviorism and thus focuses mainly on outcomes, meaning that there is a lack of attention to cognition and constructivist theories of learning that are both rooted in modern human psychology and widely accepted to explain how people learn (Cobb & Bowers, 1999). The root problems of information and knowledge dissemination within and across a firm are commonly addressed by professionals and academics in education and performance improvement. Their extensive research into these areas has covered many topics and developed theories that can help organizations and strategic management academics better understand why behaviors that harm knowledge generation or sharing occur and how best to overcome them.

The underlying logic of organizational performance and strategic management are similar and stem from human cognitive limits. The perspective of educational theorists is rooted in individual and social cognitions, rather than behavioral science. As Fiol and Lyles (1985) noted, regarding their analysis of the conceptualization of the discrepancy between cognition and behavior, “It is essential to note the difference between cognition and behavior, for not only do they represent two different phenomena, but also one is not necessarily an accurate reflection of the other” (p. 806). To date, the authors in organizational learning have synthesized the internal research and literature from the business discipline, which is grounded primarily in behaviorism, to explain firm learning, focusing mainly on observable external outcomes, rather than what occurs in the mind (Crossan et al., 2011; Nonaka et al., 2006).

This organizational learning theory development approach makes the prediction of future individual and group actions difficult, and this is because traditional behaviorist theory rejects examining what occurs in the mind because it is unobservable (Burton et al., 2004; van Bruggen, 2005), although it is aligned with the outcome-oriented views of broader business theory (Hoskisson et al., 1999). More recently, advances in psychology allow for a more analytic discussion of how individual information gathering takes place. This approach relies on decades-old information processing theory that describes the mind as a computer or machine (Hodgkinson & Healy, 2011; Tversky, 1984; Warren & Wakefield, 2011). Because business theory tends to focus on outcomes, behaviorist frameworks dominate explanations of how firms learn. These frameworks are incomplete because they do not explain how employee cognition occurs and can be used by firms for organizational performance improvement.

2.3. Current Views of Organizational Learning

Organizational learning, as it is currently defined, is the process of acquiring or generating new knowledge to improve firm performance (Almeida et al., 2016). Successful organizational learning leads to improved skills in creating, acquiring, and transferring knowledge. Then, managers develop professional development training to disseminate knowledge that is intended to modify employee behavior in response. Organizational learning processes should result in the acquisition of new competence and new knowledge application that enhance the performance of an existing activity or help employees understand better approaches by which to prepare for or adapt to changing circumstances (Crossan & Apaydin, 2010; Easterby-Smith et al., 2000; Huber, 1991). Firm learning allows for more effective adaptation to changing environmental conditions (Nonaka et al., 2006). Benefits from organizational learning should be apparent and measurable, and, at a minimum, these positive outcomes for the firm may come in the form of more efficient or more effective human resource allocation and may also generate significant innovations and the improved distribution of physical or financial resources, thereby resulting in savings or increased financial returns from applying superior knowledge, compared with rivals.

The core challenge is that the current view of organizational learning focuses on the behavioral or knowledge outcomes of individual learning without describing the process by which humans learn individually or socially. Without such a learning model, it is impossible to structure employee daily tasks or institutional units to accommodate the needs of individual cognition and knowledge formation or the socially constructed knowledge creation that follows to ensure that it is valuable beyond a single instance in the mind of a single employee. While the behavioral results are observable and, therefore, desired by leaders and managers, such performance outcomes are only detectable cumulatively. This situation leaves internal stakeholders without knowledge of the components of the process that led to these outcomes, making it difficult to determine why, when, where, or how to improve different aspects of the learning process for individuals, groups, or the whole firm. Therefore, it is crucial to have theories of what takes place in employees’ minds and how firm managers can influence or support it to achieve desired outcomes. The following section presents a knowledge creation process that is explained by the way cognition takes place in the context of learning. These concepts were tested through research, albeit in fields outside of business and performance improvement.

2.4. Learning Theory at the Individual Level

Multiple learning theories in education have been developed since John Dewey’s (2011) conceptions in the early 20^th century, and some or all can help describe how firms acquire or construct new knowledge. While many more are outside the scope of this paper, three widely accepted learning theories include behaviorist, cognitivist or cognitive processing, and constructivist theory (Sternberg & Sternberg, 2012). This review begins with behaviorist concepts and their limitations, as many readers will be familiar with them because they have been widely employed in business theory regarding organizational learning. The other theories must be discussed to frame how learning transfers from individuals across the organization.

2.5. Behaviorism and Learning

Most closely associated with Skinner (1972), behaviorism views the mind as a black box of existing internal connections that respond to external environmental stimuli. Simple stimuli generally result in simple responses from the human involved (Sternberg & Sternberg, 2012), as when receiving a paper cut, a person will pull his or her hand away to avoid the painful stimulus. Pulling away the hand is the observable behavioral response; it is an action that protects the hand and thus is desirable for the organism’s integrity. If the stimulation occurs each time the person touches paper, they become conditioned to avoid paper in the future, creating a response that is employed for continued protection from injury.

Other desired behaviors that are proactively helpful can be engendered and strengthened through reinforcement. This reinforcement occurs when a reward is given consistently after the behavior is performed, thereby increasing the strength of the connection between the stimulus, action, and outcome (Driscoll, 2000). If chronologically associated closely enough, adding another stimulus that is unrelated to a Pavlovian one (e.g., ringing a bell when silence is required, tied to a natural reward) can teach links between desired behaviors and strengthen the relationship to the original stimulus. This situation is especially the case if the behavior is deemed naturally rewarding, such as the sound of a can opening followed by the presentation of food.

The elimination or extinction of behaviors by punishing or not rewarding certain behaviors while supporting others through reinforcement is often called shaping, which leads to extinguishing an undesirable, conditioned behavior. Another process, called chaining, follows shaping. This process occurs when related or unrelated stimuli are paired with and reinforce the desired behavior (e.g., the presentation of food immediately after the opening of a can) until the organism perceives them as interrelated, thereby leading to a positive outcome (Sternberg & Sternberg, 2012). In behaviorism, chaining leads to the appearance of complex thought processes that Skinner (1972) and others believed to be illusory. Applying these concepts to an organization is difficult because the individuals learn and share what they learn with local peers. While the firm itself is not an organism, it cannot learn independently from stimulus, response, chaining, or extinguishing acts within a set of conditions given by an instructor.

The essence of theoretical behaviorism is that instructors and trainers seek to change the target learner’s observed behaviors, and an abstract institution is a collection of learners who must not only communicate what they learned but also capably judge whether they should do so interpersonally. Skinnerian (1972) behaviorists may have once lacked interest in developing a theory of what takes place in the mind during the stimulus and response-based learning process; however, modern behavioral scientists have moved beyond this limited view (Duffy & Cunningham, 1996). Today’s educational psychologists increasingly seek to create a framework that explains the process by which the mind interprets external signals, processes information, generates meaning, and develops new knowledge that can be acted upon by individuals or groups (National Research Council, 2000; Sternberg & Sternberg, 2012). Behavioral outcomes remain necessary for evaluating individual employee performances, yet understanding the employee’s decision-making and learning process is often as crucial to improving organizational performance in the long term (Crossan et al., 2008). Therefore, it is essential to develop an explanatory framework that is rooted in research and considers how learning occurs in the mind, especially regarding how people learn individually or through social processes that lead to new knowledge construction among groups. Incorporating research-based practices into organizational learning can help managers structure organizations in a way that fosters employee innovations that lead to a firm’s sustained growth (Crossan & Apaydin, 2010).

Current views of organizational learning need a more precise explanation of how individual employees learn and, therefore, how firms should best support organizational learning from a single person to groups of employees (e.g., teams, departments) and then across the company. While outcome-oriented and in line with the values of the business discipline, it is problematic to employ behaviorism as a primary means of explaining organizational learning because there needs to be an explanation for why employee learning leads to innovation. Behaviorist research and educational interventions are typically focused on a single subject because of improvement in the theory; therefore, learning performance is expected only for the person for whom an educational program is designed. The outcomes of that single subject are not generally applicable to other learners because the antecedent conditioning for each is different. Individual learners focus on observable outcomes, which makes behaviorist explanations of organizational learning challenging when developing training programs or organizational changes because of the need for more generalizability. Most attempts to use behaviorism are inefficient because of the single-subject nature of teaching and learning.

Second, to use a metaphor, an organizational strategist who focuses only on the behavioral outcomes of an organization is akin to a doctor who seeks to cure a patient only by treating observable symptoms, yet the patient returns with no improvement. The failure of the patient to improve is because there was no analysis or explanation of the systemic root causes that could be addressed. Rather than surgery, a better treatment option may be changing the person’s activities, diet, situation, or other factors that are not always readily observable but led to the disease. Organizations are similar; the symptoms of falling profits, lowered productivity, and lost clients to rival firms indicate problems. If managers make the wrong efforts to improve because they fail to understand why, how, or when these problems began, there will be no or limited improvement. In the long term, those symptoms will persist until a systemic view of the firm is taken. By doing so, improved decision-making options become available, such as applying systemic changes to the climate, culture, professional development support, personnel, or operations that can lead to a better-functioning organization (Bai et al., 2014; Janczak, 2005). There must be an attempt to understand the process and conditions under which the patient reached these observable outcomes, which requires a theory of how that occurred. Outside of traditional behaviorism, that attempt is called cognitive theory (Lim et al., 2019; Sternberg & Sternberg, 2012), and, in education, it has a longstanding relationship to explain how people at the individual and group levels come to acquire or construct new knowledge.

3.1. Cognitive Theory and a Science to Explain Learning: From Individual to Organization

According to Sternberg & Sternberg (2012), as a discipline, “cognitive psychology is the study of how people perceive, learn, remember, and think about information” (p. 3). Cognitivists believe that what takes place in the mind is of central importance to the explanation of observable behavior and can be used to guide decision-making about the design of training experiences. Therefore, learning and teaching require that researchers seek to understand the processes by which information is brought into the mind, processed into memory, and employed in the world to an observable effect: behavior. When applied to education, cognitive theory tries to answer why and how people learn (Bransford et al., 2012; National Research Council, 2000). The goal is to support learners in their active involvement in the acquisition of information or knowledge, and cognitive science is the systematic study of how people think, testing cognitive theory by following the requirements of the scientific method.

3.1.1. Cognitive Theories Structures and Processes

For many theorists and educators, behaviorism could not explain the complexity of how learning takes place in naturalistic settings, such as work environments (Driscoll, 2000; Sternberg & Sternberg, 2012). Part of the challenge is that if enough behaviors are chained together and reinforced strongly enough, then they appear to be a new, undifferentiated whole. This situation makes discriminating between the original stimulus and responses challenging, if not impossible, to separate and create the conditions needed to alter exhibited behaviors. This complex situation makes developing training for learners through conditioning difficult because the conditioned response that one might exploit extinguishes one behavior and establishes another as an automated set of responses within a larger, unobservable whole, thereby making up a learner’s experience.

In some instances, they were exploiting the process of internalizing and storing memory, in which multiple memories are influenced by a single stimulus or, sometimes, multiple stimuli, making access to that knowledge difficult. Performance improvement professionals will not understand why it is difficult to control such outcomes if they have no testable theory regarding the mental processes of a trainee that can be employed to shape desired performance outcomes. Without understanding how the mind works, instructors, managers, and designers often falsely assume why a behavior occurred. Suppose that decision-makers use a described outcome to explain the complex process by which learning will consistently arise. In that case, they cannot accurately predict the future behaviors of individuals, much less the future behaviors of entire organizations. Therefore, learning and training decisions likely fail to support intended innovation outcomes. Simple models are helpful for rapid decisions; complex models that explain how humans think, not just behave, are valuable for making organizational changes that support learning.

Memory responses may begin as simple stimuli and responses, as presented in the example. It should be noted that with increased human activity complexity, the language and practices of behaviorism lose their abilities to explain because they have no theory of what occurs in human minds (Sternberg & Sternberg, 2012). Producing complex learning outcomes through behaviorist approaches could be more efficient for educators and managers who are seeking to support whole-firm learning. The trend towards cognitivism that followed was not an outright rejection of the utility of behaviorism; behaviorism retains its value for training psychomotor skills, such as riding a bicycle or learning to read. Theorists have identified the limits of behaviorism and pointed to a gap in our understanding of how people learn, requiring a theory of how the human mind processes new information and then judges whether knowledge should be used for personal or group profit. Dissatisfaction with behaviorist explanations of how individuals and groups of people learn resulted in attempts to explain how the mind works. Through these theories, these efforts concurrently simplified our understanding of how the brain works by classifying neurological responses into groupings with acceptable internal and external logic tied to brain structures and how they must function to produce particular observable outcomes.

In the cognitive scientists’ view of the mind, as presented by Sternberg & Sternberg (2012), cognitive theory minimally includes mental structures and the processes of visual perception, auditory discernment, attention and consciousness, language, memory, knowledge organization, problem-solving and creativity, and decision-making and reasoning. In Figure 2, these cognition components are bridged with organizational learning to explain them as a cyclical process, starting with an information search in response to an assigned or discovered problem.

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Each mental process occurs either separately in rapid sequential order or interactively between processes. Once sufficient information is brought into working memory, individuals can explain their experiences with the world and act meaningfully within it. Another way to explain this is that parts of our brain perceive the outside world through visual, auditory, and other sensory stimuli, as behaviorists describe more generally. In this cognitive process, a human attends to this external data and internalizes it, thereby bringing it into short-term memory. If the person actively uses it, then this brings the data into working memory, thereby reinforcing connections within the new information and helping to organize it meaningfully. This learning approach allows the learner to connect to existing information that is stored in long-term memory, thereby allowing new actions to occur.

Once organized, the mind shifts the information from short-term and working memory into long-term storage through this information processing structure, which many theorists use a computer metaphor to explain. The brain is not a computer, and our decision-making processes do not have the limited logic of digital systems. Instead, people rely on mental shortcuts to speed their judgments by using cognitive heuristics that introduce a bias toward specific patterns of thought and behavioral outcomes based on what worked best in past experiences, thereby lowering the cognitive load but leading to increased decision-making errors.

3.1.2. Cognitive Heuristics, Learning, and Decision-Making

Managers and strategists rely on simple cognitive heuristics or rules of thumb, rather than deep considerations of their implications or intricate calculations, to guide them (Hauser, 2014). Time constraints often lead to decision-making shortcuts using limited information sources (Payne et al., 1993). The term heuristic comes from the Greek language and means to find. In cognitive psychology, it is deemed a “useful shortcut, an approximation, or a rule of thumb for searching through a space of possible solutions” (Hoffrage & Reimer, 2004, p. 439). Making the best decision with the least information is a familiar approach that managers take to respond to the rapidly increasing business cycles that are typical in today’s global economy. Such decision-making is efficient and sometimes necessary in a continuously changing market with dynamic competition and rising consumer demands. Unfortunately, these heuristic methods can lead to poor decisions that are based on narrow views in which employees are encouraged to do things as they have always done. Regular poor decision-making can develop institutional inertia that has both necessary, positive productivity outcomes, such as process standardization, but it can also lead to firm inflexibility and failures in management strategy that result from relying on doing things as they have always been, thereby leaving ineffective methods in place rather than leveraging valuable innovations and capabilities growth. This situation results in institutional lethargy and the calcification of thinking among managers, which is evident in the collapses of companies like GE (Cohan, 2022) and Sears/Kmart (Brea-Solís & Grifell-Tatjé, 2019).

To date, the work regarding cognitive heuristics in management and strategy has mainly focused on those forms of heuristics that the authors believe are most likely to influence decision-making (Hodgkinson & Healey, 2011; Kahneman & Tversky, 1984; 1979; Yang, 2015). Complex impacts on decision-making that emerge from many different forms of cognition, social interaction, and environmental factors are concurrently ongoing as humans evaluate possible choices. As such, there may be many other identified heuristics in the psychology literature that a manager may not have contemplated but should have considered when a strategy was developed or employed. This situation may be responsible for the success or failure of an approach. The decisions made by an individual manager at the meso-system level (e.g., department, team) should be included in the analysis that relates day-to-day implementation to macro-level firm strategy. This approach can help researchers understand how lower-level management’s cognitive heuristics impact the implementation of broad strategy by either supporting or impeding the leadership’s vision. Beyond individual cognitive heuristics, many strategic management decisions are made collaboratively by multiple stakeholders, each with a different power level and voice in the decision-making process. A common group-level heuristic is called groupthink, in which the whole team of employees in a unit thinks the same way about problems, solutions, and daily tasks, which leads them to avoid challenging their assumptions and practices. Table provides group-related cognitive heuristics that should be considered in the analysis of team, department, division, and firm-level performance when seeking to understand the success or failure of strategy and how best to approach performance improvement.

TABLE Selection of Unit or Group-Level Cognitive Heuristics, Reasoning, and Outcomes Affecting Group Decision-Making

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These group-level heuristics, like those for individuals, result from cognition that is geared toward solving problems quickly and efficiently. It should be noted that using any of these heuristics too often can lead to poor decision-making, providing research analysts with specific points to examine during a review of strategic failures and related potential systemic problems of interest. Further, group heuristics often result from shared cognition, which can be described with learning theories that are focused on knowledge that is produced through social interaction and new knowledge construction, usually centered on problem-solving.

3.2. Constructivism Explaining Social Knowledge Production

Duffy and Cunningham (1996) described constructivism as an umbrella term for a wide diversity of views: “[many theorists take] the general view that (1) learning is an active process of constructing rather than acquiring knowledge, and (2) instruction is a process of supporting that construction rather than communicating knowledge” (p. 2). In the constructivist worldview, truth and reality are relative to each learner and are shaped by their each learner’s experiences and conceptions of what constitutes knowledge (Elder-Vass, 2012). By contrast, Walker (2015) explained social constructivism as a knowledge construction process that is employed by groups that construct a world of experience and make meaning of it, emphasizing language as the primary conduit by which meaning is made. By contrast, radical constructivists view knowledge and truth as created, not discovered by the mind, and concern themselves with what is known about the human social experience, not objective realities of the natural world.

In constructivist conceptions of how people learn, there is also an increasingly dominant constructivist view that focuses on the cultural embeddedness of learning, employing the methods and framework of cultural anthropology to examine how learning and cognition are distributed in the environment, rather than stored in the head of an individual (Walker, 2015, p. 6). Such views that knowledge is culturally embedded and situated in the world are like those expressed in the organizational behavior literature (Cook & Yanow, 1993, Lin & Dang, 2017; Nonaka et al., 2006). In contrast, the social constructivist view adopts a cognitive science framing in which individuals interact with mental representations that are constructed by an originating individual. These are shared with others to allow for the construction of new knowledge to support problem-solving and new concept development.

4.1. A Cognitive Science-Based Process Model of Organizational Learning

The following model integrates an evaluation of cognitive heuristics into the evaluation component that is present in most business strategy implementation processes. Figure 3 depicts three interrelated components that explain how cognition and learning are distributed across an organization from the micro level (i.e., an individual employee) to the macro level (i.e., a whole firm).

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The process starts at the top left of the figure in Step 1a. Here, an individual employee discovers the need to gain new information. Once an individual employee’s knowledge discovery or creation process concludes and they believe that there is valuable new knowledge to share, the following components in the figure depict a typical organizational knowledge dissemination process. Local peers first vet the shared knowledge in a unit for utility and value through shared social cognition and discourse. The process continues with the new knowledge being shared more broadly among larger groups (e.g., departments, divisions) to establish whether the new, organized information and knowledge propositions now constitute group knowledge that is of value to the whole firm or at least to a large segment. Finally, the figure depicts the point at which a bridging of individual employee and whole group knowledge construction occurs in a manner that allows for strategy development. At this point, knowledge that is constructed through the cognitions of a single employee is transformed into capabilities that can be used to improve organizational performance or to generate new products and services that result in an increased firm competitive advantage. Once organizational performance improves due to the dissemination of the new knowledge, other employees may develop further revisions to that knowledge that can improve the firm’s performance (Step 3e), thereby starting the improvement cycle again at Step 1a.

4.2. Cognitive Science Theory Enacted in Firm-Level Propositions from the Proposed Models

The following are propositions that will be explored in future qualitative research as a means of expanding upon the ideas described here. From those data, the authors will further refine the model. Once the model has additional support from direct observation, interviews, and other means, quantitative methodologies will be applied to test the theoretical connections and generate future hypotheses.

4.2.3. Proposition 3: Company Strategy Requires Leaders to Identify How Far Knowledge Should Travel

While the knowledge resulting from individual and group learning may be valuable for an individual department, that unit may be as far as it needs to be disseminated. Doing so requires leaders to judge whether knowledge retains value beyond improving the performance of their direct reports or is applicable organization-wide. Managers must know whether to retain newly acquired knowledge as a resource for local performance or if it should be disseminated more broadly to support the firm’s competitive advantage. Each aspect of the model is linked visually in Figure 4, which explores how managers can analyze learning in their organizations as a part of strategy development to support organization knowledge acquisition or construction, mirroring the traditional make or buy decision.

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