Importance of Public Relation and Communication Essay Example
Importance of Public Relation and Communication Essay Example

Importance of Public Relation and Communication Essay Example

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  • Pages: 12 (3277 words)
  • Published: July 14, 2018
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The academic work called "A Dynamic Theory of Collaboration: A Structural Approach to Facilitating Intergovernmental Use of Information Technology", authored by Laura J. Black, Anthony M. Cresswell, Theresa A. Pardo, Fiona Thompson, Donna S. Canestraro, Meghan Cook, Luis F. Luna, Ignacio J. Martinez, David F. Andersen and George P. Richardson from Montana State University, Center for Technology in Government and Rockefeller College of Public Affairs and Policy provides a comprehensive examination into the elements of trust development, teamwork enhancement and knowledge distribution within a multi-governmental project focused on the establishment of an innovative information system.

The authors use research and a case study to create a system dynamics model and simulate different scenarios. They examine how trust, knowledge sharing, and facilitation skills impact cross-boundary trust and collaboration. Trust, knowledge sharing, and collaboration are important in in


terorganizational relationships.

These elements are crucial in the interactions between organizations, particularly in innovative or new business process projects. The objective of this research is to design a dynamic model that investigates the interplay among trust, collaboration, and knowledge sharing within such a project. The end goal is to develop a communal information system for both public and private entities. By devising this model, we hope to intensify our conceptual and pragmatic understanding of trust, collaboration, and knowledge sharing in IT projects across different organizations.

The Center of Technology in Government (CTG) research team and the Rockefeller College modeling group have collaborated for approximately a year to develop a model inspired by effective collaborative procedures. This document represents their second effort, supported by National Science Foundation grant #SES-9979839. The perspectives and conclusions presented in thi

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paper are solely those of the authors and should not be interpreted as reflecting the views or policies of the National Science Foundation.

The study associates confidence with understanding a collaborator's role and goals in the context of a collaborative project. This paradigm implies that learning is achieved when discussion techniques and elements like project management apparatuses and IT system needs analysis documents, referred to as "boundary objects" [9], are efficiently merged through meeting facilitation. In different theoretical viewpoints and research fields, the concepts of trust, knowledge dispersion, and teamwork are closely intertwined.

The concept of trust as a fundamental aspect of social order is studied in various fields and levels of analysis [29]. Both interpersonal and interorganizational trust are seen as crucial elements for successful and coordinated interaction in different contexts [17, 50], such as efficient teamwork [25] and collaboration between organizations [27, 23]. However, as highlighted by Porter [see 32], trust is often discussed and assumed to be beneficial for organizations, similar to the way weather and motherhood are widely talked about.

In organizational context, there is some vagueness when it comes to defining trust. Different conceptions of trust are used to shape that aspect in the model. The model also takes a broad approach to understanding knowledge sharing and collaboration. Knowledge sharing can take explicit forms or be tacit and embedded in action, groups, procedures, and artifacts. This can vary significantly across communities of practice. Sharing knowledge may also have different costs and difficulties [11, 52, 49, 26].

The research and theorizing related to collaboration across problematic organizational boundaries is the subject of this work. The study focuses on collaboration

in an information technology project and incorporates research on project dynamics and work flows. This paper contributes to the understanding of interorganizational collaboration by integrating trust, knowledge sharing, and project flow in a dynamic framework. The project under investigation is a multigovernment and interorganizational initiative involving state, county, and city regulatory agencies, as well as nonprofit and local government service providers supported by the State. The project aims to develop a shared management information system for the Bureau of Housing Services (State of New York) and state-funded homeless shelter providers. This system will assist in managing and evaluating client service programs. The Bureau of Housing Services (BHS) determines funding eligibility and need for services, and offers case management, direct services, and referrals to external service providers. The total expenditure on federal, state, and local government programs for the homeless in New York State is approximately $350 million per year, with $130 million allocated to client services.The BHS, the New York City Department of Homeless Services, provider representatives, and the Center for Technology in Government (CTG) collaborated on the project work.

The project involved two main responsibilities for CTG: assisting and promoting collaboration among the other participants, and supplying IT expertise and a development environment for the prototype system. In order for the project to succeed, it was crucial for individuals from the state agency overseeing shelters to work closely with managers from various homeless shelters in New York City, Westchester, and Suffolk counties. Throughout a period of over two years, the project participants successfully achieved the required collaboration and exchanged intricate operational knowledge.

The creation and evolution of a successful prototype system for

shared information [14] resulted in major achievements. Challenges like potential abuse of power, violations of client privacy, variances in business procedures, diverse viewpoints on data elements and their respective definitions, as well as inconsistency in IT platforms were successfully tackled by the team members. The model scrutinizes and elucidates the linkages between collaboration, trust, and sharing of knowledge. However, these complex phenomena are still subjects of dispute with no globally recognized framework to interpret their interplay.

The model outlined in this text utilizes the principles of system dynamics work in project management to analyze the interplay among the organizations engaged in the creation of the HIMS. The model operates under the assumption that cooperative efforts are influenced by a sequence of reinforcing procedures tied to understanding one's own and others' responsibilities, requirements, limitations, and goals within the project. Concepts of collaboration, knowledge dissemination, and trust draw from various perspectives examined later in the text. 3.1 The viewpoint of project management

Research utilizing system dynamics modeling has offered valuable insights into various issues related to the project in question. Cooper's [13] investigation of change orders in a ship-building project and Abdel-Hamid's [1] study of a software development effort explicitly depict how problems emerge, are identified, and resolved during project work, and their impact on the punctuality and quality of the finished project. They also demonstrate that insufficient allocation of resources at the beginning of a project can lead to an increasingly urgent need for resources in later stages of the project.

Research conducted by Repenning [37] and furthered by Repenning, Goncalves, and Black [38] examined how resources are distributed in multiple product development

endeavors. Their findings revealed a tendency to favor urgent deadlines at the expense of adequate staffing during early project stages, potentially diminishing overall work quality within the entity. Trust is identified as an important aspect in interorganizational contexts, serving as a management tool [2, 35, 36]. It can encourage standards of mutual benefit and transparency that promote social regulation and coordination - both essential for effective collaboration and knowledge exchange. Nonetheless, there is still a lack of agreement on trust's types or definitions across different disciplines including anthropology, economics, organizational behavior, psychology, sociology [43].

Some recurring themes are vulnerability, risk, and the significance of positive expectations or optimistic belief [42]. Trust lacks meaning without uncertainty and risk [43]. Behaviors involving trust expose individuals to increased vulnerability from the trustee's behavior not being controlled. Collaboration, trust, and knowledge sharing: A project perspective 2 Throughout the innovation project described here, the agency name was modified from Bureau of Shelter Services (BSS) to Bureau of Housing Services (BHS).

The use of “BHS” in this paper refers to the same agency as the earlier BSS. Proceedings of the 36th Hawaii International Conference on System Sciences (HICSS’03) 0-7695-1874-5/03 $17. 00 © 2002 IEEE the trustor’s control [51]. If the trustee abuses this vulnerability, the damage is greater than the benefit if trust is fulfilled. Thus trust can be seen as the expectation that the trustee will not behave opportunistically, even if there are incentives to do so [10, 24, 33]. Several forms of trust can be seen in different relationships [29, 43].

A particular framework [42] divides trust into three categories relevant to this project: Calculus-based trust

(that depends on the capability of the person placing their trust to assess reliability [43], as well as, the propensity of the trusted party to reciprocate that trust [31]); Identity-based trust (rooted in emotional or personal relationships developed over a series of mutual interactions [28, 53]); and Institution-based trust (stemming from institutional elements like organizational culture, societal norms, and legal systems which reduce risk and nurture trust [30, 53, 44, 45]).

Trust can be seen in the actions and events in this project, with the model combining these forms of trust in each party's trust of one another. Trust is important for effective information sharing, organizational learning, and knowledge and information sharing in interorganizational relationships. Feedback dynamics play a role in determining whether interactions across boundaries are collaborative.

The notion of relative expertise evolves over time. Based on the structuration theories [6,21], everyday life is perceived as a repetitive process where the gathered values and attributes, also known as "capital," of entities or individuals shape daily activities. These actions can either sustain or modify the actors' accumulated capital. The method of system dynamics modeling proves to be effective in illustrating the interplay between activities and accrued capital over certain periods.

Upon concluding two group-modeling sessions [14], the team was able to successfully build an initial model using these methodologies.

We utilized qualitative data from the case to develop an enhanced model for analyzing the observed collaborative dynamics and advancing theories on the connections between collaboration, trust, knowledge, and communication facilitation tools. System dynamics was chosen as the modeling method because it has been effective in studying intricate feedback systems,

where feedback is seen as a closed sequence of causal relationships.

The main idea is that dynamic behaviors, which refer to performance over time, are strongly connected to the structure of feedback loops. Exploring and comprehending the connections between behavior and structure helps to explain and effectively intervene in dynamic, nonlinear processes that result from various interrelationships within a system. Similar to grounded theory, an inductive formal model is created by drawing conclusions about causal relationships based on data, which generates a specific observed behavior pattern in the field. [19] [22, 47]

The process of model-building involves representing hypotheses using connected elements of a model structure, simulating the structure, comparing the simulated behavior to the observed behavior in the field, and refining the hypotheses by changing the structure based on the data. Therefore, a formal model that is based on data is a non-textual representation of a theory that explains the cause-and-effect relationships responsible for producing the observed behavior patterns in the field [4].

We interviewed several CTG staff members who were part of the original HIMS case. They confirmed that the variables and interrelationships proposed in the model structure are accurate, and also validated the directional aspects of the simulations. Simulations serve as a useful tool to assess the internal consistency of multiple interrelationships, which cannot be achieved through text-based arguments alone. Furthermore, simulations allow for the exploration of a wider range of circumstances beyond those observed in real-world scenarios.

The text discusses the model used to analyze collaboration and knowledge sharing. Cook and Brown differentiate between knowledge as something possessed by individuals or groups and knowing as knowledge-in-practice. The project focuses

on tacit knowledge, which is embedded in the social context and more challenging to transfer. This type of knowledge is closely tied to the work culture and the social construction of the work processes within each organization.

Knowledge can also be seen as a phenomenon at the organization level, existing within organizational forms, social expertise, and as "knowledge-in-practice situated in the historical, sociomaterial, and cultural context in which it occurs" [11, 20, 49]. Zander and Kogut [52] discovered five aspects of a company's knowledge: codifiability, teachability, complexity, system dependence, and product observability. These aspects are expected to influence the transferability and imitability of the knowledge. The use of system dynamics modeling has allowed researchers to study how knowledge contributes to the creation of collaborative patterns of interaction.

According to the work of Black, Carlile, and Repenning [5] based on a case study by Barley [3], the expertise of workers in different roles dynamically influences the allocation of tasks and the knowledge distribution. Black [4] examined collaboration in new product development and presented a theory on how location, timing, and the use of artifacts in cross-departmental interactions impact work-related knowledge and project progress. Again, relative expertise plays a significant role in social processes. Proceedings of the 36th Hawaii International Conference on System Sciences (HICSS’03) -7695-1874-5/03 $17. 00 © 2002 IEEE explore the range of outcomes resulting from variations in initial project knowledge, trust, and the effectiveness of boundary objects used by CTG's facilitation tools and methods. We believe that if the same interplay among knowledge, trust, and collaboration can plausibly generate multiple behavioral patterns under different parameter settings, the modeled theory may explain various

observed dynamics in the field. 5.

Model description 5. 1 Model overview The model (documentation available from authors Black or Luna) focuses on reinforcing dynamics: collaborating enhances understanding of one's own and the other's work; as familiarity increases, trust is built; and as trust grows, sharing more information improves the effectiveness of collaborative work. In this study, the Center for Technology in Government researchers highlight the importance of facilitative tools and methods in collaborative work.

The proposed information system will undergo stakeholder analyses and facilitated conversations to identify problems and clarify objectives. IT requirements analysis and data modeling tools, along with Collaboratively Doing Project Work + R, will serve as boundary objects to make interdependencies between the parties understandable and concrete. These tools will also help find and correct errors in the collaborative work. The HIMS project involved one State agency and approximately 120 local service providers, going through two significant phases of information system development: specification discovery and prototype construction.

In the model, we simplify the simulated dynamics by making significant assumptions. We group all the serviceprovider agencies together and depict them as a single Provider. We focus only on the initial phase of system development, which is joint specification discovery. (We intend to include more of the project's complexities in our future work.) Furthermore, we depict CTG's facilitation as external parameters that impact the quality and effectiveness of work done collectively by the State and Provider.

Thus, there is a model that involves two main participants, the State and the Provider, who are working on developing specifications for a proposed information system called HIMS. This model includes three

main parts: a simple project model that represents the dynamics of doing work, the accumulation of knowledge by each participant about their own work and the other's work, and the resulting trust and engagement that drives the continued development of the specifications. Additionally, there is an emphasis on the facilitative design of the meetings' process and content by CTG, which influences the overall project.

State's Knowledge of State's Role in the Project + Provider's Knowledge of State's Role in the Project + Provider's Knowledge of Provider's Role in the Project + Project Work R + Learning by Doing Sense of Progress in Project + Initial Trust to Commence Work + Tools that Facilitate Knowledge Elicitation and Communication + CTG Facilitative Methods and Tools

Figure 1: This is an overview of the model, which shows four states: Work to Do, Undiscovered Rework, Known Rework, or Work Really Done. At the beginning of the specification development phase, no work has been done yet, so all tasks (Project Definition) are in the Work to Do accumulation. As participants perform work (assuming that all specification development work happens in meetings between the State and Provider), tasks are moved to the stock Work Really Done. The probability of this movement is 1 minus the Error Fraction. The Error Fraction is 5.2 in this case. Project work progress is represented by the model sector shown in Figure 2.

Numerous studies in system dynamics have been conducted on project management [13, 18, 40], leading to the establishment of a standard model structure for representing project fundamentals [46], which we utilize in this context. Within projects, tasks can fall into

one of two categories. The Proceedings of the 36th Hawaii International Conference on System Sciences (HICSS'03) 0-7695-1874-5/03 $17.00 © 2002 IEEE highlights the impossibility of executing all tasks flawlessly on the first attempt. Specification-discovery tasks that are executed incorrectly necessitate rework, and require additional collaboration between the State and the Provider to determine which tasks need to be redone.

Therefore, when the State and Provider engage in Work to Do, tasks can end up in the accumulation of Undiscovered Rework with a certain likelihood of Error Fraction. Likewise, redoing troublesome tasks can either be accomplished accurately (progressing from the accumulation of Known Rework to Work Really Done) or inaccurately (reverting back to Undiscovered Rework), depending on the error fraction. This process involves performing new work correctly (moving from Work Really Done to doing new work right) or incorrectly (moving from Work Really Done to doing new work wrong), as well as transforming the ability to perform rework from doing rework wrong to doing rework right. Ultimately, learning occurs through recognizing problems while engaging in undiscovered rework and addressing them through known rework.

Figure 2 represents the engagement degree displayed by project members, which is strongly connected to their determination to stick with the project work (see below). This dedication is largely dependent on their perception of how the project is advancing. The Sense of Progress, demonstrated in Figure 3, relies on elements like the conviction that a part of tasks has been achieved up to now, updates about overall advancement of the project, how speed at work affects comprehension of progress and recent attempts made by participants.

These measures offer a positive

perspective, demonstrating a typical inclination (seen both in professional settings and everyday situations) to assume that any task completed is done correctly, unless the need for revision arises. The perception of progress heavily influences the perceived weight of work yet to be done (see Figure 3: Sense of Progress 5.3). Collaboration, engagement, trust, and knowledge of one's own work and that of others are all interconnected factors. According to the model, collaboration is the result of participants' level of engagement. As engagement and collaboration increase, productivity also rises.

The level of engagement a participant exhibits is influenced by their sense of progress and the trust they have for their counterpart. This trust stems from comprehending each other's roles, needs, goals, and restrictions in relation to project execution. As everyone collaboratively works, they garner a better understanding of their individual contribution as well as an increased awareness of the parts others play in the project. In this context, two entities - The State and The Provider - can acquire two types of knowledge through collaboration on information system specifications. Each entity has the chance to deepen their understanding about their own roles, needs, objectives, and constraints within the project (The State’s Perception of its Role & Provider's Understanding of its Role). Furthermore, they are able to gain insights into how the other party contributes to the project (State's Perspective on Provider's Contribution & Provider's Recognition of State’s Role). These acquired understandings are represented as dimensionless variables limited within a scale ranging from 0 to 1.

Comprehending one's own obligations within a project reduces the likelihood of errors. A profound understanding of individual roles by

all participants greatly diminishes the risk of mistakes during teamwork. This concept is highlighted at the 36th Hawaii International Conference on System Sciences (HICSS'03), emphasizing how trust and active participation are vital for successful collaborative projects. An effective team relies on trust in the provider, knowledge about each other's tasks, and an understanding of the project’s objectives. Additionally, being aware of personal responsibilities and grasping partners' work scope are essential elements to consider.

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