Shopping for Computer Restaurant Management Systems

A myriad of computer management systems are available for the restaurant business. The author discusses all aspects of evaluating, purchasing, and using such systems for a restaurant operation.

Evaluating the Success of Lodging Yield Management Systems

Although there are more than 7,000 properties using lodging yield management systems (LYMSs), both practitioners and researchers alike have found it difficult to measure their success. Considerable research was performed in the 1980s to develop success measures for information systems in general. In this work the author develops success measures specifically for LYMSs.

Essays in Empirical Operations Management: Bayesian Learning of Service Quality and Structural Estimation of Complementary Product Pricing and Inventory Management

This dissertation contributes to the rapidly growing empirical research area in the field of operations management. It contains two essays, tackling two different sets of operations management questions which are motivated by and built on field data sets from two very different industries --- air cargo logistics and retailing.

The first essay, based on the data set obtained from a world leading third-party logistics company, develops a novel and general Bayesian hierarchical learning framework for estimating customers' spillover learning, that is, customers' learning about the quality of a service (or product) from their previous experiences with similar yet not identical services. We then apply our model to the data set to study how customers' experiences from shipping on a particular route affect their future decisions about shipping not only on that route, but also on other routes serviced by the same logistics company. We find that customers indeed borrow experiences from similar but different services to update their quality beliefs that determine future purchase decisions. Also, service quality beliefs have a significant impact on their future purchasing decisions. Moreover, customers are risk averse; they are averse to not only experience variability but also belief uncertainty (i.e., customer's uncertainty about their beliefs). Finally, belief uncertainty affects customers' utilities more compared to experience variability.

The second essay is based on a data set obtained from a large Chinese supermarket chain, which contains sales as well as both wholesale and retail prices of un-packaged perishable vegetables. Recognizing the special characteristics of this particularly product category, we develop a structural estimation model in a discrete-continuous choice model framework. Building on this framework, we then study an optimization model for joint pricing and inventory management strategies of multiple products, which aims at improving the company's profit from direct sales and at the same time reducing food waste and thus improving social welfare.

Collectively, the studies in this dissertation provide useful modeling ideas, decision tools, insights, and guidance for firms to utilize vast sales and operations data to devise more effective business strategies.

Service Quality in Arts Events: Operations Management Strategies for Effective Delivery

Recent debate on the quality of arts events has concentrated on the requirement to deliver against a complex range of political, social, and cultural criteria with an emphasis on the external partnerships that are forged. Yet those aspects of quality over which event organizers have more direct control have been accorded minor examination. The authors believe that operational effectiveness is key to service quality in the cultural context, and seek to demonstrate that a balanced consideration of both process and product is vital to fully deliver quality arts events. This article identifies areas of emergent research and practice and focuses on issues in the front-of-house environment where the breakdown of service quality is a real concern, using the experience of one UK not-for-profit arts organization as a case study to illustrate potential management responses.

The role of Lean at the interface with between operations management and applied services within a large aerospace organisation: a boundary spanning perspective

Increased complexity in large design and manufacturing organisations requires improvements at the operations management (OM)–applied service (AS) interface areas to improve project effectiveness. The aim of this paper is explore the role of Lean in improving the longitudinal efficiency of the OM–AS interface within a large aerospace organisation using Lean principles and boundary spanning theory. The methodology was an exploratory longitudinal case approach including exploratory interviews (n = 21), focus groups (n = 2), facilitated action-research workshops (n = 2) and two trials or experiments using longitudinal data involving both OM and AS personnel working at the interface. The findings draw upon Lean principles and boundary spanning theory to guide and interpret the findings. It was found that misinterpretation, and forced implementation, of OM-based Lean terminology and practice in the OM–AS interface space led to delays and misplaced resources. Rather both OM and AS staff were challenged to develop a cross boundary understanding of Lean-based boundary (knowledge) objects in interpreting OM requests. The longitudinal findings from the experiments showed that the development of Lean Performance measurements and lean Value Stream constructs was more successful when these Lean constructs were treated as boundary (knowledge) objects requiring transformation over time to orchestrate improved effectiveness and in leading to consistent terminology and understanding between the OM–AS boundary spanning team.

Taxonomy of Institutional Issues that Act as Barriers to the Implementation of Pavement Management Systems, 1994

The benefits of pavement management system when fully implemented are well known and the history of successful implementation is rich. Implementation occurs, for purposes of this paper, when the pavement management system is the critical component for making pavement decisions. This paper addresses the issues that act as barriers to full implementation of pavement management systems. Institutional barriers, not technical and financial barriers, are more commonly responsible for a pavement management systems falling short of full implementation. The paper groups these institutional issues into a general taxonomy. In general, more effort needs to be put forth by highway agencies to overcome institutional issues. Most agencies approach pavement management as a technical process, but more commonly, institutional issues become more problematic and thus require more attention paid to institutional issues. The paper concludes by summarizing the implementation process being taken by the Iowa Department of Transportation. The process was designed to overcome institutional barriers and facilitate the complete and full implementation of their pavement management system.

Model based integration of management systems (MSs) – case study

Abstract Purpose – The purpose of this paper is to present a case study regarding the deployment of a previously developed model for the integration of management systems (MSs). The case study is developed at a manufacturing site of an international enterprise. The implementation of this model in a real business environment is aimed at assessing its feasibility. Design/methodology/approach – The presented case study takes into account different management systems standards (MSSs) progressively implemented, along the years, independently. The implementation of the model was supported by the results obtained from an investigation performed according to a structured diagnosis that was conducted to collect information related to the organizational situation of the enterprise. Findings – The main findings are as follows: a robust integrated management system (IMS), objectively more lean, structured and manageable was found to be feasible; this study provided an holistic view of the enterprise’s global management; clarifications of job descriptions and boundaries of action and responsibilities were achieved; greater efficiency in the use of resources was attained; more coordinated management of the three pillars of sustainability – environmental, economic and social, as well as risks, providing confidence and added value to the company and interested parties was achieved. Originality/value – This case study is pioneering in Portugal in respect to the implementation, at the level of an industrial organization, of the model previously developed for the integration of individualized MSs. The case study provides new insights regarding the implementation of IMSs including the rationalization of several resources and elimination of several types of organizational waste leveraging gains of efficiency. Due to its intrinsic characteristics, the model is able to support, progressively, new or revised MSSs according to the principles of annex SL (normative) – proposals for MSSs – of the International Organization for Standardization and the International Electrotechnical Commission, that the industrial organization can adopt beyond the current ones.

BUILDING EFFICIENT AND COST-EFFECTIVE CLOUD-BASED BIG DATA MANAGEMENT SYSTEMS

In today’s big data world, data is being produced in massive volumes, at great velocity and from a variety of different sources such as mobile devices, sensors, a plethora of small devices hooked to the internet (Internet of Things), social networks, communication networks and many others. Interactive querying and large-scale analytics are being increasingly used to derive value out of this big data. A large portion of this data is being stored and processed in the Cloud due the several advantages provided by the Cloud such as scalability, elasticity, availability, low cost of ownership and the overall economies of scale. There is thus, a growing need for large-scale cloud-based data management systems that can support real-time ingest, storage and processing of large volumes of heterogeneous data. However, in the pay-as-you-go Cloud environment, the cost of analytics can grow linearly with the time and resources required. Reducing the cost of data analytics in the Cloud thus remains a primary challenge. In my dissertation research, I have focused on building efficient and cost-effective cloud-based data management systems for different application domains that are predominant in cloud computing environments. In the first part of my dissertation, I address the problem of reducing the cost of transactional workloads on relational databases to support database-as-a-service in the Cloud. The primary challenges in supporting such workloads include choosing how to partition the data across a large number of machines, minimizing the number of distributed transactions, providing high data availability, and tolerating failures gracefully. I have designed, built and evaluated SWORD, an end-to-end scalable online transaction processing system, that utilizes workload-aware data placement and replication to minimize the number of distributed transactions that incorporates a suite of novel techniques to significantly reduce the overheads incurred both during the initial placement of data, and during query execution at runtime. In the second part of my dissertation, I focus on sampling-based progressive analytics as a means to reduce the cost of data analytics in the relational domain. Sampling has been traditionally used by data scientists to get progressive answers to complex analytical tasks over large volumes of data. Typically, this involves manually extracting samples of increasing data size (progressive samples) for exploratory querying. This provides the data scientists with user control, repeatable semantics, and result provenance. However, such solutions result in tedious workflows that preclude the reuse of work across samples. On the other hand, existing approximate query processing systems report early results, but do not offer the above benefits for complex ad-hoc queries. I propose a new progressive data-parallel computation framework, NOW!, that provides support for progressive analytics over big data. In particular, NOW! enables progressive relational (SQL) query support in the Cloud using unique progress semantics that allow efficient and deterministic query processing over samples providing meaningful early results and provenance to data scientists. NOW! enables the provision of early results using significantly fewer resources thereby enabling a substantial reduction in the cost incurred during such analytics. Finally, I propose NSCALE, a system for efficient and cost-effective complex analytics on large-scale graph-structured data in the Cloud. The system is based on the key observation that a wide range of complex analysis tasks over graph data require processing and reasoning about a large number of multi-hop neighborhoods or subgraphs in the graph; examples include ego network analysis, motif counting in biological networks, finding social circles in social networks, personalized recommendations, link prediction, etc. These tasks are not well served by existing vertex-centric graph processing frameworks whose computation and execution models limit the user program to directly access the state of a single vertex, resulting in high execution overheads. Further, the lack of support for extracting the relevant portions of the graph that are of interest to an analysis task and loading it onto distributed memory leads to poor scalability. NSCALE allows users to write programs at the level of neighborhoods or subgraphs rather than at the level of vertices, and to declaratively specify the subgraphs of interest. It enables the efficient distributed execution of these neighborhood-centric complex analysis tasks over largescale graphs, while minimizing resource consumption and communication cost, thereby substantially reducing the overall cost of graph data analytics in the Cloud. The results of our extensive experimental evaluation of these prototypes with several real-world data sets and applications validate the effectiveness of our techniques which provide orders-of-magnitude reductions in the overheads of distributed data querying and analysis in the Cloud.

Learning Management Systems (LMS) and e-learning management: an integrative review and research agenda

Information Technology (IT) can be an important component for innovation since enabling e-learning it can provide conditions to which the organization can work with new business and improved processes. In this regard, the Learning Management Systems (LMS) allows communication and interaction between teachers and students in virtual spaces. However the literature indicates that there are gaps in the researches, especially concerning the use of IT for the management of e-learning. The purpose of this paper is to analyze the available literature about the application of LMS for the e-learning management, seeking to present possibilities for researches in the field. An integrative literature review was performed considering the Web of Science, Scopus, Ebsco and Scielo databases, where 78 references were found, of which 25 were full papers. This analysis derives interesting characteristics from scientific studies, highlighting gaps and guidelines for future research.

Standardized environmental management systems as an internal management tool

In a principal-agent model we analyze the firm’s decision to adopt an informal or a standardized Environmental Management System (EMS). Our results are consistent with empirical evidence in several respects. A standardized EMS increases the internal control at the cost of introducing some degree of rigidity that entails an endogenous setup cost. Standardized systems are more prone to be adopted by big and well established firms and under tougher environmental policies. Firms with standardized EMS tend to devote more effort to abatement although this effort results in lower pollution only if public incentives are strong enough, suggesting a complementarity relationship between standardized EMS and public policies. Emission charges have both a marginal effect on abatement and a qualitative effect on the adoption decision that may induce a conflict between private and public interests. As a result of the combination of these two effects it can be optimal for the government to distort the tax in a specific way in order to push the firm to choose the socially optimal EMS. The introduction of standardized systems can result in win-win situations where firms, society and the environment get better off.

Entrepreneurship in project management systems: proposal of a model and preliminary empirical evidence

This study analyzes the manifestation of the dimensions of Entrepreneurial Orientation (EO) and Project Management Systems (PMS). We used a qualitative approach to conduct exploratory research through a study in literature and a pilot case in a software company. Data was collected from semi structured interviews, documents, and records on file, then triangulated and treated with content analysis. The model proposed for the relationship between the types of PMS (ad hoc, Classic PM, innovation, entrepreneurship/intrapreneurship) and the dimensions of EO (innovativeness, risk-taking, proactiveness, competitive aggressiveness, and autonomy), was partially corroborated by empirical studies. New studies are suggested to validate the applicability and setup of the model.

The exploration of potato-associated bacteria in the Central Andean Highlands and their application in integrated crop management systems

Potato is the most important food crop after wheat and rice. A changing climate, coupled with a heightened consumer awareness of how food is produced and legislative changes governing the usage of agrochemicals, means that alternative more integrated and sustainable approaches are needed for crop management practices. Bioprospecting in the Central Andean Highlands resulted in the isolation and in vitro screening of 600 bacterial isolates. The best performing isolates, under in vitro conditions, were field trialled in their home countries. Six of the isolates, Pseudomonas sp. R41805 (Bolivia), Pseudomonas palleroniana R43631 (Peru), Bacillus sp. R47065, R47131, Paenibacillus sp. B3a R49541, and Bacillus simplex M3-4 R49538 (Ecuador), showed significant increase in the yield of potato. Using – omic technologies (i.e. volatilomic, transcriptomic, proteomic and metabolomic), the influence of microbial isolates on plant defence responses was determined. Volatile organic compounds of bacterial isolates were identified using GC/MS. RT-qPCR analysis revealed the significant expression of Ethylene Response Factor 3 (ERF3) and the results of this study suggest that the dual inoculation of potato with Pseudomonas sp. R41805 and Rhizophagus irregularis MUCL 41833 may play a part in the activation of plant defence system via ERF3. The proteomic analysis by 2-DE study has shown that priming by Pseudomonas sp. R41805 can induce the expression of proteins related to photosynthesis and protein folding in in vitro potato plantlets. The metabolomics study has shown that the total glycoalkaloid (TGA) content of greenhouse-grown potato tubers following inoculation with Pseudomonas sp. R41805 did not exceed the acceptable safety limit (200 mg kg-1 FW). As a result of this study, a number of bacteria have been identified with commercial potential that may offer sustainable alternatives in both Andean and European agricultural settings.

AgroDB - integration of database management systems with crop models.

2016