This exploratory case study positions the 2004-05 National Hockey League (NHL) lockout as an organizational crisis, studying it within a Situational Crisis Communication Theory (SCCT) frame. A mixed methodology approach used qualitative and quantitative content analyses and a survey of NHL fans to gauge the NHL's reputation five years after the lockout. For the content analyses, 282 newspaper articles from 7 newspapers in the U.S. and Canada were coded for SCCT variables and presentation of the lockout by news writers. NHL fans (n = 140) were surveyed with the goal of assessing SCCT variables as predictors of attitude. Results confirmed previous SCCT findings and showed links between SCCT variables and fan attitudes toward the NHL and the sport of hockey.

En undersökning av byrån Mustasch utifrån identitet, profil och image som sedan kopplats samman med teorier gällande legitimitet och reputation management. Metoderna för denna undersökning var en kvantitativ innehållsanalys samt enkät med utrymme för kvalitativa tolkningar. Undersökningen visade att Mustasch har ett starkt varumärke och bygger upp det med hjälp av samtliga delar i teorin, med visst utrymme för utveckling.

Problemformulering och syfte: Att företag använder sig av influencers i sin marknadsföring blir allt vanligare. Influencers är populära för dess trovärdighet och unika relation till följarna. Men deras trovärdighet är också deras svaghet, då misstag och kritik riskerar att påverka en influencers anseende till det negativa. Det saknas dock forskning om hur influencers bör agera när de väl utsätts för kritik eller drabbas av en kris då majoriteten av forskningen utgår ifrån ett organisationsperspektiv. Syftet med studien är därför att undersöka hur influencers genom sin kommunikation hanterar situationer och händelser som riskerar att påverka deras anseende, exempelvis en potentiell kris. Studien är en beskrivande fallstudie som ser närmare på 19 influencers som i olika sammanhang drabbats av en kris eller kritiserats och granskats både i traditionell och sociala medier på olika sätt. Undersökningen grundar sig i teorier om kriskommunikation och reputation management.    Metod och material: Studien har genomförts med hjälp av en kvalitativ innehållsanalys av 19 stycken influencers kommunikation i sociala medier. Materialet består av instragram-inlägg, instagram-stories, blogginlägg, tidningsartiklar och youtube-videos Huvudresultat: Resultatet visade att sättet influencers kommunicerar i samband med kriser och kritik skiljer sig mellan olika personer. Influencers använder sig av kris-kommunikationsstrategier men utan ett tydligt tillvägagångssätt. Att behålla relationen till följarna framstår som viktigare än att matcha strategin till upplevd kris.

Syfte: Studiens syfte är att undersöka sambandet mellan intern och extern corporate social responsibility samt hur den sociala hållbarhetsprestationen påverkas av de interna dimensionerna av corporate social responsibility i europeiska försäkringsbolag. Tidigare studier har undersökt sambandet mellan intern och extern CSR, men inte i försäkringsbranschen och sällan inkluderat sambandets orsaker eller intern CSR:s dimensioner. Metod: Studien tillämpar en kvantitativ forskningsstrategi med en positivistisk forskningsfilosofi och en hypotetiskt-deduktiv ansats. Studiens forskningsdesign är longitudinell och data för perioden 2009–2019 för 48 europeiska försäkringsbolag används. Data är sekundärdata hämtad från Thomson Reuters Datastream, analyserad i statistikprogrammet SPSS.  Resultat & slutsats: Studiens resultat visar ett positivt samband mellan intern och extern CSR samt att intern CSR:s dimension anställda påverkar försäkringsbolagens sociala hållbarhetsprestation positivt. Detta förklaras teoretiskt genom knowledge management vilket är särskilt påtagligt i kunskapsintensiva företag.  Examensarbetets bidrag: Studien bidrar med kunskap inom ämnet CSR i försäkringsbranschen samt utökar kunskapen kring samspelet mellan intern och extern CSR i kunskapsintensiva branscher genom knowledge management. Studien visar hur ett fokus på anställdas välbefinnande kan öka den sociala hållbarhetsprestationen. Förslag till fortsatt forskning: Det vore intressant att undersöka det funna sambandet med andra metoder för jämförelse och att undersöka sambandet med längre tidsförskjutning för att visa påverkan på längre sikt. Intressant vore också att djupare undersöka intern CSR:s dimensioner och dess parametrar.

SAMMANFATTNING Datum:                      2024-05-29   Nivå:                          Kandidatuppsats i företagsekonomi, 15 Hp Institution:                 Akademin för Ekonomi, Samhälle och Teknik, Mälardalens Universitet Författare:            Nimo Mahamed Elmi          Hoodo Muhumud             Nimo Hassan                                                         02/07/13                           02/07/05                     02/03/02 Titel:                          Rykteshantering inom banksektorn.  Handledare:               Dariusz Osowski Nyckelord:                 Rykteshantering, digitalisering, AI, legitimitet, RMT Forskningsfråga:       Hur har digitaliseringen, speciellt artificiell intelligens påverkat                               hanteringen av svenska bankers digitala rykte?  Syfte:       Syftet med studien är att utforska fenomenet rykte och dess hantering i en digitaliserad affärsmiljö. Utgångspunkten för studien är att göra en fördjupad undersökning av hur AI har påverkat hanteringen av ryktesrisker. Metod:     Uppsatsen är en kvalitativ studie med strukturerad intervjumetod. Insamlingen av empirin gjordes genom intervjumetodik och gör empirin primärkälla. Slutsats:     AI och digitaliseringen generellt har förändrat banksektorn på många sätt. Bland   annat övervakningen där avancerade algoritmer och system används för att förbättra säkerheten och hanteringen av ryktesrisker. Den har också effektiviserat bankernas arbetsprocess och avlastat personalens arbetsbörda. Slutligen har den även ökat banktillgängligheten genom att erbjuda kunderna digitala plattformar som förenklat kommunikationen mellan organisation och intressent. Genom dessa strategier etablerar bankerna en hållbar digital närvaro. / ABSTRACT Date:           2024-05-29 Level:        Bachelor thesis in Business Administration, 15 cr Institution:       School of Business, Society and Engineering, Mälardalen University Authors:         Nimo Mahamed Elmi                     Hoodo Muhumud                 Nimo Hassan                                                               02/07/13                         02/07/05                      02/03/02 Title:                      Reputation management in banking sector. Supervisor:             Dariusz Osowski Keywords:               Reputation management, digitalization, AI, legitimacy, RMT Research question:   How has digitalization, especially artificial intelligence, affected the management of Swedish bank´s digital reputation? Purpose:                 The aim of the study is to explore the phenomenon of reputation and its management in a digitized business environment. The starting point for the study is to conduct an in-depth investigation into how AI has affected the management of reputational risks. Method:              The study is a qualitative study with a semi structured interview method. The collection of the empirical evidence was done through interview methodology and makes the empirical evidence a primary source. Conclusion:         AI and digitization in general have changed the banking sector in many ways. Among other things, monitoring where advanced algorithms and systems are used to improve security and the management of reputational risks. It has also streamlined the banks' work process and relieved the staff's workload. Finally, it has also increased banking accessibility by offering customers digital platforms that have simplified communication between organization and stakeholders. Through these strategies, the banks establish a sustainable digital presence.

This thesis investigates both theoretical and practical aspects of the design and analysis of iterative algorithms for trust and reputation management and recommender systems. It also studies the application of iterative trust and reputation management mechanisms in ad-hoc networks and P2P systems. First, an algebraic and iterative trust and reputation management scheme (ITRM) is proposed. The proposed ITRM can be applied to centralized schemes, in which a central authority collects the reports and forms the reputations of the service providers (sellers) as well as report/rating trustworthiness of the (service) consumers (buyers). It is shown that ITRM is robust in filtering out the peers who provide unreliable ratings. Next, the first application of Belief Propagation algorithm, a fully iterative probabilistic algorithm, on trust and reputation management (BP-ITRM) is proposed. In BP-ITRM, the reputation management problem is formulated as an inference problem, and it is described as computing marginal likelihood distributions from complicated global functions of many variables. However, it is observed that computing the marginal probability functions is computationally prohibitive for large scale reputation systems. Therefore, the belief propagation algorithm is utilized to efficiently (in linear complexity) compute these marginal probability distributions. In BP-ITRM, the reputation system is modeled by using a factor graph and reputation values of the service providers (sellers) are computed by iterative probabilistic message passing between the factor and variable nodes on the graph. It is shown that BP-ITRM is reliable in filtering out malicious/unreliable reports. It is proven that BP-ITRM iteratively reduces the error in the reputation values of service providers due to the malicious raters with a high probability. Further, comparison of BP-ITRM with some well-known and commonly used reputation management techniques (e.g., Averaging Scheme, Bayesian Approach and Cluster Filtering) indicates the superiority of the proposed scheme both in terms of robustness against attacks and efficiency. The introduction of the belief propagation and iterative message passing methods onto trust and reputation management has opened up several research directions. Thus, next, the first application of the belief propagation algorithm in the design of recommender systems (BPRS) is proposed. In BPRS, recommendations (predicted ratings) for each active user are iteratively computed by probabilistic message passing between variable and factor nodes in a factor graph. It is shown that as opposed to the previous recommender algorithms, BPRS does not require solving the recommendation problem for all users if it wishes to update the recommendations for only a single active user using the most recent data (ratings). Further, BPRS computes the recommendations for each user with linear complexity, without requiring a training period while it remains comparable to the state of art methods such as Correlation-based neighborhood model (CorNgbr) and Singular Value Decomposition (SVD) in terms of rating and precision accuracy. This work also explores fundamental research problems related to application of iterative and probabilistic reputation management systems in various fields (such as ad-hoc networks and P2P systems). A distributed malicious node detection mechanism is proposed for delay tolerant networks (DTNs) using ITRM which enables every node to evaluate other nodes based on their past behavior, without requiring a central authority. Further, for the first time. the belief propagation algorithm is utilized in the design and evaluation of distributed trust and reputation management systems for P2P networks. Several schemes are extensively simulated and are compared to demonstrate the effectiveness of the iterative algorithms and belief propagation on these applications.

This essay examines corporate reputation and reputation management online, where destinations were selected as an example of a reputation-dependent industry with special terms. The aim of this study is to examine how Swedish destinations strategically manage their reputation online. Furthermore, the thesis sees into six destinations in Sweden using a theoretical approach on how companies work with their reputation to prevent and nurture their reputation online from a public relations perspective. The result showed that the destinations work actively online to maintain their reputation. Their primary critical stakeholders are politicians and their visit nutrition, their secondary stakeholders are in the long term their own residents. The result also showed that the digitalization has led to both challenges and opportunities. There is thus, an internal challenge in finding resources and an external challenge to compete globally. The destinations determinedly work to measure and monitor their reputation online, but see management as complex today. This study concludes that some areas of online reputation management are found to be applicable for companies in general, but mainly Swedish destinations. In conclusion the study presents a model on how companies proactively can manage their reputation from a public relations point of view.

O pojmu reputation management bylo dlouhou dobu slyšet převážně v oblasti marketingu ve spojení s budováním brandu. S rozvojem sociálních médií se na trhu objevily nástroje měřící osobní reputaci, jež kvantifikují uživatelovu interaktivitu na základě několika proměnných. Ty našly své uplatnění v rukou nepočetných social media profesionálů a geeků. Jak ale k řízení osobní reputace v sociálních sítích přistupují běžní uživatelé? Jak hodnotí reputaci členů svých sociálních sítí a jak se tyto poznatky odráží na jejich vlastním projevu? Tato práce se snaží nalézt cestu k zodpovězení těchto a dalších otázek. Principy kvalitativního přístupu se obrací k samotnému jádru tohoto procesu - tvůrcům a hodnotitelům osobní reputace a sociálním interakcím, jimiž se uskutečňuje. Abstract Reputation management is a notion which thus far has surfaced mainly in the field of marketing in relation to brand building. Following the expansion of social media, various personal reputation measuring tools have offered quantitative analyses of users' interactivity on the basis of several variables available on the market. However, these tools were useful for a limited group of social media professionals and enthusiasts. But how do average users approach personal reputation management on social networking sites? How do they...

Trust is the cornerstone of success in any relationship between two or more parties. Generally, we do not socialize, seek advice, consult, cooperate, buy or sell goods and services from/to others unless we establish some level of mutual trust between interacting parties. When e-commerce was merging infancy, the concept of trusting an entity in a virtual world was a huge obstacle. Gradually, increasingly-sophisticated, largely generic reputation scoring and management systems were embedded into the evolving marketplaces. Current technologies to include cloud computing, social networking, and mobile applications, coupled with the explosion in storage capacity and processing power, are evolving large-scale global marketplaces for a wide variety of resources and services, such as Amazon.com, BitTorrent, WebEx and Skype. In such marketplaces, user entities, or users for short; namely, consumers, providers and brokers, are largely autonomous with vastly diverse requirements, capabilities and trust profiles. Users' requirements may include service quality levels, cost, ease of use, etc. Users' capabilities may include assets owned or outsourced. Trustors' profiles may include what is promised and commitments to keep these promises. In such a large-scale heterogeneous marketplace, the trustworthy interactions and transactions in services and resources constitute a challenging endeavor. Currently, solving such issues generally adopts a "one-size fits all" trust models and systems. Such approach is limiting due to variations in technology, conflicts between users' requirements and/or conflicts between user requirements and service outcomes. Additionally, this approach may result in service providers being overwhelmed by adding new resources to satisfy all possible requirements, while having no information or guarantees about the level of trust they gain in the network. Accordingly, we hypothesize the need for personalizable customizable Trust Management Systems (TMSs) for the robustness and wide-scale adoption of large-scale marketplaces for resources and services. Most contemporary TMSs suffer from the following drawbacks: • Oblivious to diversities in trustors' requirements, • Primarily utilize feedback and direct or indirect experience as the only form of credentials and trust computations, • Trust computation methodologies are generally hardcoded and not reconfigurable, • Trust management operations, which we identify as monitoring, data management, analysis, expectation management, and decision making, are tightly coupled. Such coupling impedes customizability and personalization, and • Do not consider context in trust computations, where trust perspectives may vary from a context to another. Given these drawbacks and the large scale of the global marketplace of resources and services, a reference architecture for trust management systems is needed, which can incorporate current systems and may be used in guidance and development of a wide spectrum of trust management systems ranging from un-personalized to fully personalized systems. Up to our knowledge, no TMS reference architecture exists in the literature. In this dissertation, we propose a new Reference Architecture for Trust Management (RATM). The proposed reference architecture applies separation of concern among trust management operations; namely, decision expectation, analytics, data management and monitoring. RATM defines trust management operations through five reconfigurable components which collectively can be used to implement a wide spectrum of trust management systems ranging from generic to highly personalized systems. We used RATM for trust personalization, where we propose a Personalized Trust Management System (PTMS) based on RATM. We evaluated PTMS's scalability and demonstrated its effectiveness, efficiency and resilience by contrasting against a Generic Trust Management System (GTMS). We used two case studies for our evaluations; namely, BitTorrent and a video conferencing application. Intellectual Merit In this work, we propose RATM, a reference architecture for trust management systems that can be used to implement a wide variety of trust management systems ranging from generic systems (un-personalized) to highly personalized systems. We assume service-based environment where consumers, brokers and service providers are interacting and transacting in services and resources to satisfying their own trust requirements. We used RATM to implement a personalized trust management system (TMS). The main contributions of this work are as follows: • Proposing RATM for the guidance and development of a wide spectrum of TMSs ranging from un-personalized to fully personalized systems, and • Utilizing our RATM to propose and implement a personalized, scalable TMS with varying trust computation models. Broader Impact RATM provides reference architecture for trust management which can be used to develop and evaluate a wide spectrum of TMSs. Personalization, in general, paves the road for reaching high levels of satisfaction, where interacting parties' requirements are individually considered and thus consumers are served the best suited service(s). Hence, we claim that PTMS would largely enhance large-scale heterogeneous systems offering services and resources. This could lead to more cooperation, more transactions, more satisfaction, less malicious behavior and lower costs. / PHD / Trust is the cornerstone of success in any relationship between two or more persons. Generally, we do not socialize, seek advice, consult, cooperate, buy or sell goods and services from/to others unless we establish some level of mutual trust between interacting parties. When ecommerce was firstly used, the concept of trusting a service delivered by someone who is not physically in the same place was a huge obstacle. Gradually, more sophisticated, largely generic reputation scoring and management systems were used into the new internet marketplaces. A reputation scoring and management system is a system which collects feedback from different users about service providers in a certain marketplace on the internet and uses them to anticipate future behavior of these providers. Current computer technologies to include cloud computing, social networking, and mobile applications, coupled with the explosion in computer and mobile devises’ storage capacity and processing power, are evolving large-scale global marketplaces offering a wide variety of resources and services to consumers across the globe. Examples include Amazon.com, BitTorrent, WebEx and Skype. In such marketplaces, consumers, providers and brokers, are largely autonomous with vastly diverse requirements, capabilities and trust profiles. By autonomous we mean acting in accordance with one's moral duty rather than one's desires. Users’ requirements may include service quality levels, cost, ease of use, etc. Users’ capabilities may include assets owned or leased from others. Trustors’ profiles may include what is promised and commitments to keep these promises. In such a large-scale marketplace, the trustworthy interactions and transactions in services and resources constitute a challenging endeavor. By trustworthy interaction we mean transactions which deliver results that are accepted by all parties. Currently, solving such issues of trust generally adopts a “one-size fits all” trust models and systems. By trust models and systems we mean computer programs which perform the reputation scoring and management. i.e. select a single service which can serve all requirements. Such approach is limiting due to variations in technology, conflicts between users’ requirements and/or conflicts between user requirements and service outcomes. Additionally, this approach may result in service providers being overwhelmed by adding new resources to satisfy all possible requirements, while having no information or guarantees about the level of trust they gain in the eye of their consumers. Accordingly, we hypothesize the need for personalizable customizable Trust Management Systems (TMSs) for the robustness and wide-scale adoption of large-scale marketplaces for resources and services. In other words, we assume the need for a trust management system which can select services satisfying transaction parties’ requirements. Most contemporary TMSs suffer from the following drawbacks: • Select one size fits all service, • Utilize one and only one type of data for calculating the score used for anticipating the future behavior of a party, • Utilize one and only one method to calculate the score value used for anticipating the future behavior of a party, • Trust scoring calculation method does cannot be reprogrammed, • Trust scoring calculation method does not consider the context in which the data was collected. Given these drawbacks and the large scale of the global marketplace of resources and services, a reference architecture for trust management systems is needed, which can incorporate current systems and may be used in guidance and development of a wide spectrum of trust management systems ranging from un-personalized to fully personalized systems. Up to our knowledge, no TMS reference architecture exists in the literature. In this dissertation, we propose a new Reference Architecture for Trust Management (RATM), which overcomes the drawbacks of current systems. It proposes evaluating trust by number of flexible operations namely, decision expectation, analytics, data management and monitoring. These operations collectively can be used to implement a wide spectrum of trust management systems ranging from generic to highly personalized systems. We used RATM for trust personalization, where we propose a Personalized Trust Management System (PTMS) based on RATM. We evaluated PTMS’s ability to sustain the increasing number of users and demonstrated its effectiveness, efficiency and its ability to resist attacks. We achieved that by contrasting experimentation results against that of a Generic Trust Management System (GTMS). We used two case studies for our evaluations; namely, BitTorrent and a video conferencing application.

Master of Science / Department of Communications and Agricultural Education / Jason D. Ellis / Agricultural sustainability is a growing concern for the general public because of agriculture’s considerable use of land, water, and other natural resources. In response to this growing concern, companies have started to publish sustainability reports to highlight sustainable practices. The purpose of this study was to examine the role of sustainability reporting from companies in the agri-food supply chain. The research objectives of this study were (1) determine the prevalence of sustainability reporting among food system companies, (2) identify, to what extent, the three components of the triple bottom line model are represented in sustainability reports, (3) determine if/how sustainability reporting differs among sectors of the agriculture supply chain, (4) assess how companies describe stakeholder engagement in sustainability reports, and (5) explore which aspects of reputation are included in sustainability reports. In total, 66 agribusinesses were included in this study of which 16 had published sustainability reports. Data for the quantitative content analysis were collected using a scorecard based on the Global Reporting Initiative (GRI) guidelines. Results indicated that sustainability reporting is limited among companies involved in the agriculture and food supply chain. Though better than sectors studied in previous research, agribusinesses also struggle to explain stakeholder engagement and need to focus sustainability report content to align more closely with the three components of the triple bottom line model – environment, economic, and social.