Restaurant Industry Perspectives on Pro-social Rule Breaking: Intent versus Action

The resounding message extracted from the service literature is that employees serve pivotal functions in the overall guest experience. This is of course due to the simultaneous delivery of personalized service provision with resultant consumption of those services. This simultaneous delivery and consumption cycle is at times challenged by a perceived desire to accommodate guest request that may violate, to a greater or lesser degree, an organizational rule. This is important to note because increased interactions with customers enable frontline employees to have a better sense of what customers want from the company as well as from the company itself (Bitner, et al, 1994). With that platform established, then why are some employees willing to break organizational rules and risk disciplinary action to better service a customer? This study examines the employee personality, degree of autonomy, job meaning, and co-worker influence on an employee's decision to break organizational rules. The results of this study indicate that co-worker influence exerted a minimal influence on employee decision to break rules while the presence of societal consciousness exerted a much stronger influence. Women reported that they were less likely to engage in rule divergence, and significant correlations were present when filtered by years in current position, and years in the industry.

Database As A Tool For Hospitality Management

In his discussion - Database As A Tool For Hospitality Management - William O'Brien, Assistant Professor, School of Hospitality Management at Florida International University, O’Brien offers at the outset, “Database systems offer sweeping possibilities for better management of information in the hospitality industry. The author discusses what such systems are capable of accomplishing.” The author opens with a bit of background on database system development, which also lends an impression as to the complexion of the rest of the article; uh, it’s a shade technical. “In early 1981, Ashton-Tate introduced dBase 11. It was the first microcomputer database management processor to offer relational capabilities and a user-friendly query system combined with a fast, convenient report writer,” O’Brien informs. “When 16-bit microcomputers such as the IBM PC series were introduced late the following year, more powerful database products followed: dBase 111, Friday!, and Framework. The effect on the entire business community, and the hospitality industry in particular, has been remarkable”, he further offers with his informed outlook. Professor O’Brien offers a few anecdotal situations to illustrate how much a comprehensive data-base system means to a hospitality operation, especially when billing is involved. Although attitudes about computer systems, as well as the systems themselves have changed since this article was written, there is pertinent, fundamental information to be gleaned. In regards to the digression of the personal touch when a customer is engaged with a computer system, O’Brien says, “A modern data processing system should not force an employee to treat valued customers as numbers…” He also cautions, “Any computer system that decreases the availability of the personal touch is simply unacceptable.” In a system’s ability to process information, O’Brien suggests that in the past businesses were so enamored with just having an automated system that they failed to take full advantage of its capabilities. O’Brien says that a lot of savings, in time and money, went un-noticed and/or under-appreciated. Today, everyone has an integrated system, and the wise business manager is the business manager who takes full advantage of all his resources. O’Brien invokes the 80/20 rule, and offers, “…the last 20 percent of results costs 80 percent of the effort. But times have changed. Everyone is automating data management, so that last 20 percent that could be ignored a short time ago represents a significant competitive differential.” The evolution of data systems takes center stage for much of the article; pitfalls also emerge.

Current State of Management/Union Relations in Hospitality Sector

Labor management relations in the hospitality sector is an important aspect of effective management. Increasingly, unions are becoming proactive in organizing hospitality workers. This manifests itself in strikes, boycotts, picketing, sexual harassment complaints, and complaints to OSHA regarding safety and health workplace violations. This research monitors the current scene with respect to labor management relations and analyzes work issues that have been brought up for third-party resolution by NLRB staff or arbitrators. The study reports on 66 NLRB cases and 104 arbitration cases. Issues brought before the NLRB include mostly contract interpretations. In arbitration, there were mostly discipline issues, including work rule violations, disorderly conduct, poor performance and employee theft. Quite often, the proposed job action on the part of the employer was discharge. In NLRB cases, the employee usually prevailed, while in arbitration the employer usually prevailed.

Comparing novice designer performance using a rule -based approach versus a pattern -based approach in conceptual data modeling tasks

Conceptual database design is an unusually difficult and error-prone task for novice designers. This study examined how two training approaches---rule-based and pattern-based---might improve performance on database design tasks. A rule-based approach prescribes a sequence of rules for modeling conceptual constructs, and the action to be taken at various stages while developing a conceptual model. A pattern-based approach presents data modeling structures that occur frequently in practice, and prescribes guidelines on how to recognize and use these structures. This study describes the conceptual framework, experimental design, and results of a laboratory experiment that employed novice designers to compare the effectiveness of the two training approaches (between-subjects) at three levels of task complexity (within subjects). Results indicate an interaction effect between treatment and task complexity. The rule-based approach was significantly better in the low-complexity and the high-complexity cases; there was no statistical difference in the medium-complexity case. Designer performance fell significantly as complexity increased. Overall, though the rule-based approach was not significantly superior to the pattern-based approach in all instances, it out-performed the pattern-based approach at two out of three complexity levels. The primary contributions of the study are (1) the operationalization of the complexity construct to a degree not addressed in previous studies; (2) the development of a pattern-based instructional approach to database design; and (3) the finding that the effectiveness of a particular training approach may depend on the complexity of the task.

Restaurant Industry Perspectives on Pro-social Rule Breaking: Intent versus Action

The resounding message extracted from the service literature is that employees serve pivotal functions in the overall guest experience. This is of course due to the simultaneous delivery of personalized service provision with resultant consumption of those services. This simultaneous delivery and consumption cycle is at times challenged by a perceived desire to accommodate guest request that may violate, to a greater or lesser degree, an organizational rule. This is important to note because increased interactions with customers enable frontline employees to have a better sense of what customers want from the company as well as from the company itself (Bitner, et al, 1994). With that platform established, then why are some employees willing to break organizational rules and risk disciplinary action to better service a customer? This study examines the employee personality, degree of autonomy, job meaning, and co-worker influence on an employee's decision to break organizational rules. The results of this study indicate that co-worker influence exerted a minimal influence on employee decision to break rules while the presence of societal consciousness exerted a much stronger influence. Women reported that they were less likely to engage in rule divergence, and significant correlations were present when filtered by years in current position, and years in the industry.

Event mining for system and service management

Modern IT infrastructures are constructed by large scale computing systems and administered by IT service providers. Manually maintaining such large computing systems is costly and inefficient. Service providers often seek automatic or semi-automatic methodologies of detecting and resolving system issues to improve their service quality and efficiency. This dissertation investigates several data-driven approaches for assisting service providers in achieving this goal. The detailed problems studied by these approaches can be categorized into the three aspects in the service workflow: 1) preprocessing raw textual system logs to structural events; 2) refining monitoring configurations for eliminating false positives and false negatives; 3) improving the efficiency of system diagnosis on detected alerts. Solving these problems usually requires a huge amount of domain knowledge about the particular computing systems. The approaches investigated by this dissertation are developed based on event mining algorithms, which are able to automatically derive part of that knowledge from the historical system logs, events and tickets. ^ In particular, two textual clustering algorithms are developed for converting raw textual logs into system events. For refining the monitoring configuration, a rule based alert prediction algorithm is proposed for eliminating false alerts (false positives) without losing any real alert and a textual classification method is applied to identify the missing alerts (false negatives) from manual incident tickets. For system diagnosis, this dissertation presents an efficient algorithm for discovering the temporal dependencies between system events with corresponding time lags, which can help the administrators to determine the redundancies of deployed monitoring situations and dependencies of system components. To improve the efficiency of incident ticket resolving, several KNN-based algorithms that recommend relevant historical tickets with resolutions for incoming tickets are investigated. Finally, this dissertation offers a novel algorithm for searching similar textual event segments over large system logs that assists administrators to locate similar system behaviors in the logs. Extensive empirical evaluation on system logs, events and tickets from real IT infrastructures demonstrates the effectiveness and efficiency of the proposed approaches.^