Readiness Assessment Model Research Articles

The Development of the Lean Six Sigma Readiness Assessment Model for the Hotel Sector

ABSTRACT Lean Six Sigma (LSS) implementation still shows a high failure rate. Lack of readiness is one of the causes. Readiness assessment requires special exploration of each sector, including the hotel sector, where there is still no development of an LSS readiness assessment model. This study aims to develop a readiness assessment model for LSS implementation in the hotel sector. Data processing in the readiness assessment model uses the fuzzy logic method, is translated again into linguistic terms using Euclidean distance, and is ranked using the TOPSIS approach. The literature review produced 34 Readiness Factors (RF) that were validated by eight credible hotel practitioners and used as guidelines in conducting LSS readiness assessments in the hotel sector. Case studies were conducted on Hotel A and Hotel B, which showed that Hotel A was “Very Ready” and Hotel B was “Ready” to implement LSS. This research is perhaps the first of its kind in the hotel sector. This research also uses the Delphi method to collect data on the importance level, which may not have been done in collecting data on LSS readiness in any sector.

A readiness assessment model for human systems management digitalization in industrial organizations

ABSTRACT Human systems management (HSM) in organizations must invest in digitization to remain competitive. Even though there is no denying digitalization is essential for modern industrial organizations, the success of digitalization projects is rarely contingent on chance. HSM digitalization requires more than just technology. It also requires leadership, people, strategy, innovation, and process readiness. Organizations must select the most suitable digitalization project to initiate the transition and begin by increasing and monitoring readiness for a successful transition. A practical approach to a successful transition begins with increasing and monitoring readiness. The literature suggests a lack of analytical assessment models for HSM digitalization readiness in industrial organizations, especially for small and medium enterprises (SMEs). This research presents a framework with the general best-worst method (GBWM) to examine decision criteria and help organizations, particularly SMEs, choose the most effective digitalization strategy. A case study demonstrates the applicability and efficacy of the proposed method in assessing HSM digitalization readiness in SMEs.

Effect of stage-matched educational intervention on use of institutional delivery in Northwest Ethiopia: using community readiness model.

even though there are many initiatives to improve institutional delivery, there are low service utilization and community readiness for institutional delivery in Ethiopia. This study assessed the role of community readiness on delivery service use. a pre-and post-test design with a control group was used for the evaluation of the stage-matched educational intervention following the protocol of the community readiness assessment model. Based on the baseline assessment of community readiness among 15 kebeles where the study was conducted, the overall score of nine kebeles was below stage-5 out of the nine stages, which were targeted for the intervention. The intervention group (n= three kebeles) participated in the stage-matched intervention for 15 months, while the control group (n= three kebeles) were not given the intervention. The data were analyzed using the difference in difference (DiD) method. there were significant improvements in a stage of change for the promotion of institutional delivery (p-value <0.001) and institutional delivery use (p-value <0.001) in the intervention group as compared to the control group. The study revealed that the intervention influenced community resource allocation (at marginally significant levels), improved leader-ship quality of prevention, and community climate to supportive prevention efforts. There was evidence that the intervention (health promotion) also increased service use at a significant level. the community readiness-based intervention (health promotion) can be useful to measure the combined attitude and behavior towards institutional delivery services. The village-based mobilizer approach had a positive effect on institutional delivery use and the level of community readiness on the promotion of institutional delivery.

Stochastic operation model for readiness assessment of small wind turbines based on Markov theory

AbstractWind energy is now one of the most important alternative sources of renewable energy. The development of wind power generation is a prerequisite to meet environmental and sustainable development requirements while achieving energy security goals. The condition for the effectiveness of the proper operation of a wind power plant is its ability to perform the intended functions, which can be expressed by the coefficient of technical readiness. This article presents an original analysis of the readiness of small wind turbines. As part of the research, an original stochastic operation model was developed based on the application of the Markov process theory. Based on the collected data, a 3‐state phase space of the studied process was identified. Various analyses were carried out to calculate the operating coefficients of wind power plants. The ergodic (boundary) probabilities were calculated using three methods. The conditional probabilities were then determined based on the initial distribution. The resulting readiness factors, not exceeding 30%, indicate the low operational efficiency of the small wind turbines in question. Furthermore, an analysis of the sensitivity of the performance factors was carried out for the analysed objects.

Readiness assessment for smart manufacturing system implementation: multiple case of Indian small and medium enterprises

ABSTRACT In recent times, a paradigm shift is observed in the manufacturing domain through the inception of the smart manufacturing (SM) system. Small and medium enterprises (SMEs) in developing countries are striving hard to catch up with this transition. Thus, a need arises to assess their preparedness and subsequently develop an appropriate mechanism for transition. In this context, readiness assessment is a suitable approach that clearly depicts the quantification and qualification of readiness stages through various dimensions. To this effect, this study proposes a generic readiness assessment model with 5 stages, 6 building blocks, and 22 dimensions. Furthermore, the dimensions are ranked using ‘Stepwise Weight Assessment Ratio Analysis (SWARA)’ to understand their influence on overall readiness attainment. The practical viability of the proposed readiness assessment model is tested on five Indian SMEs. Based on the readiness level of each organization, recommendations are made to further improve their preparedness for transformation. Other SMEs can utilize this tool as a self-assessment methodology to check their status and subsequently strategize their policies for future transformation.

Designing an E-learning Readiness Assessment Model for Iraqi Universities Employing Fuzzy Delphi Method.

The assessment process of readiness for adoption an educational system considers the lifeblood of the e-learning system in a particular educational organization and the ability to assess the organization's readiness among the main factors which contributes to the success and progress. The readiness models are instruments that assist educational organizations in measuring their capability level and identifying the gaps to develop a strategy for implementing and adopting e-learning system. Due to the sudden chaos that Iraqi educational institutions have been exposed to the Covid-19 epidemic since the beginning of 2020, the e-learning system has been adopted as a quick alternative educational system for the continuation of the educational process without taking into consideration the readiness of the basic components of the educational process, which comprises the readiness of the infrastructure, human and educational organization to adopt such systems. Despite increased attention by stakeholders and the government with the readiness assessment process recently, there is no comprehensive model for assessing e-learning readiness in Iraqi higher education institutions, the purpose of this study is to design a model of an e-learning readiness assessment for Iraqi universities based on the comparative studies and the experts' views. It is worth to mention that the proposed model has objectively designed according to particular features and local characteristics country. The fuzzy delphi method was utilized for the validation process of the proposed model. The main dimensions and all factors of the proposed model reached the experts' agreement except a number of measures that did not achieve the assessment requirements. The final analysis result indicates that the e-learning readiness assessment model includes 3 main dimensions and 13 factors with 86 measures. Iraqi higher educational institutions can employ the designed model to assess their readiness and identify the areas that need improvement and reduce the gaps failures in e-learning adoption.

Extending a Data Management Maturity Model for Process Mining in Healthcare.

Many components must work together to continuously improve processes in healthcare organizations. Process mining has recently developed into a discipline that can make a significant contribution here. We want to extend an existing management tool to assess and improve the capability of organizations in this area. We add a dimension to the adoption readiness assessment and maturity model for sharable clinical pathways to assess and improve event data quality. We present different approaches for formal and checkpoint assessments and an embedding of the improvement strategy with examples. The additional dimension from the process mining domain integrates with the existing model. At all levels, links can be established between the various aspects of event data quality with existing dimensions. The model has yet to be tested in a real-world use case.

Disaster readiness assessment model using integrated statistical variance and proximity value index

PurposeThe regular occurrence of natural disasters elevates the need for an effective method to measure organizational preparedness in responding to the adverse impact of disasters. In this context, this paper presents a new decision support model to assess organizational disaster preparedness using both subjective and objective disaster preparedness criteria in a multi-criteria decision-making context.Design/methodology/approachThe statistical variance method is integrated with the proximity value index (PVI) technique to determine priority scores in order to rank organizational disaster readiness.FindingsThe results of applying the integrated model developed herein enable decision-makers to make informed decisions for assigning priority ranking of organizational disaster preparedness in a simpler and more efficient way.Research limitations/implicationsHuman resource is the most impacting criterion affecting hospital preparedness in undertaking action to cure disaster victims.Practical implicationsThis paper offers an exemplar of a simple and efficient decision-making process considering the subjectivity associated with decision-making as well as the objectivity of data used for determining the priority ranking of organizational disaster preparedness.Originality/valueIntegrating statistical variance method with the PVI technique is novel and it has not been presented in previous studies. In fact, this study is the first to integrate both methods for selecting the priority ranking of organizational disaster preparedness.

Represent: A community engagement roadmap to improve participant representation in cancer early detection research: An Oregon case study.

While authentic and sustained community involvement in the research process is critically important to making new technologies and interventions effective and socially acceptable, there is uneven participation across sociodemographic, racial, and ethnic communities in many research areas, including cancer early detection research. Currently, 18% of cancer in the United States impacts Hispanics and Latinos, this population accounts for < 10% of research participants. Understanding barriers and facilitators to cancer early detection research is imperative to the ultimate success of this research. Therefore, the objectives of this study were to: understand Hispanic and Latino community perspectives in participation in cancer early detection research; and identify sustainable and mutually beneficial approaches to community engagement and involvement. The Oregon Case Study, led by Oregon Health & Science University's Community Outreach, Research and Engagement (CORE) in partnership with colleagues at Vocal, a partnership between Manchester University NHS Foundation Trust and the University of Manchester and Cambridge University, adopted a participatory research approach to better understand participation in cancer early detection research from the perspectives of Oregon's Hispanic and Latino community members. We implemented two evidence-based community engagement models, the Community Engagement Studio and the Community Readiness Assessment Model. Using a facilitated format prescribed by each community engagement model, community members helped us to answer two research questions: (1) What methods help us increase participation of underrepresented communities in cancer early detection research?; and (2) How can we build trust between researchers and underrepresented communities within cancer early detection research? Quantitative (i.e., descriptive statistic) and qualitative (i.e., thematic analysis) analytic methods were used to measure and assess community knowledge, leadership, beliefs, and resources regarding participation in cancer early detection research. A total of 36 Hispanic and Latino community members participated in the two community engagement models. We identified three emergent themes pertaining to participation in cancer early detection research that include: low-level awareness of cancer early detection research and opportunities for research participation, structural barriers to research participation, and uncertainty of the benefits of research participation. Our approach, using two evidence-based community engagement models, yielded valuable insights about perceptions of research participation for Hispanic and Latino community members. These findings, synthesized into three key themes, led to actionable recommendations to increase research participation.

Readiness Assessment Model for Mobile Learning in South African Rural High School: A Case of Limpopo Province

Readiness Assessment Model for Mobile Learning in South African Rural High School: A Case of Limpopo Province

Maturity Assessment of Industry 4.0 Implementation in Kazakhstani and Norwegian Oil and Gas Contexts

The present industrial revolution in modern history, called Industry 4.0, completely changes the vision and processes of modern production and makes it more efficient, high quality, and potentially more profitable. The spreading of Industry 4.0 across all industries did not leave behind the oil and gas sector. More developed countries such as Norway, where the oil and gas industry plays a crucial role, have already initiated Industry 4.0 transformation and progressing toward achieving higher maturity levels. At the same time, developing countries such as Kazakhstan, where the oil and gas sector is also one of the most important industries, make their initial attempts towards Industry 4.0 but in a more cut-rate way. Therefore, this study aimed to conduct a maturity assessment of the oil and gas sectors of two countries, through a new Industry 4.0 readiness assessment model (RAM), developed exclusively for oil and gas companies. As a result, the model helped to identify the current maturity level of enterprises, strengths and weaknesses, and pinpoint country-specific patterns. Although the research focuses primarily on the upstream sector, the developed model and research results can also be extended to address the needs of the midstream and downstream sectors.

The Implementation of the Conjunction of Lean Six Sigma and Industry 4.0: A Case Study in the Czech Republic

Abstract As advanced technologies are becoming a natural part of the industrial environment, the influence of these technologies on organizational practices is becoming more expanding. In this paper, an attempt was made to understand the conjunction of Lean Six Sigma and Industry 4.0. The study was conducted in the Czech Republic and qualitative data was gathered from 10 companies. The information on the benefits, weaknesses and challenges of the conjunction was summarized. For the research purposes literature review and qualitative analysis were performed. It was found out that, although the conjunction is connected with challenges, the perspectives are beneficial for industrial companies. The data generated also allowed to introduce the readiness assessment model for the implementation of the conjunction based on 4 categories: technological, managerial, financial and human. This information could be used for theoretical and practical purposes for the creation of a successful Lean Six Sigma pattern in Industry 4.0.

Adoption Readiness Assessment Model based on SaaS Maturity Level in SMEs

Abstract— The acceleration of digital transformation in the industrial revolution 4.0 triggered by Cloud Computing created an expansion of the commercialization of IT services. SaaS ERP is one of the fastest growing cloud computing services and is a solution for SMEs. Although SaaS ERP uses a cloud base, it turns out that not all vendors provide uniform services. The difference in the services provided depends on the differences in Metadata, Security and shared services. These different services can be classified in 4 SaaS maturity levels consisting of level 1: Custom/Ad Hoc, level 2: Configurable, 3: Standardization/Multi-Tenant, and level 4: Scalable and Multi-tenant. The current research on measuring SaaS ERP adoption readiness has not considered this maturity level, even though this difference will have a different impact on each adoption factor. Continuing from the previous research which formulated the factors and weights of adoption, the purpose of this study is to understand the considerations of SMEs in adopting SaaS ERP that is deployed at different maturity levels. By using expert judgment, an assessment rubric is created for each factor at each maturity level. The expert assessment produces a range maturity index which is combined with the weight of each factor to assess the maturity level of SMEs' readiness to adopt SaaS ERP. The assessment rubric developed with expert validation and SMEs can be use as a tool to measure the maturity level of SMEs' readiness to adopt SaaS ERP Keywords— Adoption Readiness, Expert Judgement, ERP, SaaS ERP, SMEs, SaaS Maturity Level

Capacity and Readiness Assessment of Healthcare Facilities for Digital Health Interventions Against Tuberculosis and HIV in Addis Ababa, Ethiopia.

BackgroundThere is a high level of concern that low-income countries lack the capacity and readiness to effectively adopt, implement, and scale up digital health interventions (DHIs). We aimed to assess the infrastructure and human resource capacity and readiness of healthcare facilities to adopt and implement any new DHI for tuberculosis (TB) and HIV care and treatment in Addis Ababa, Ethiopia.MethodWe carried out a cross-sectional, mixed-methods study in 14 public healthcare facilities that provide TB and HIV care and treatment services. Providers' perceived readiness to adopt and implement digital health was assessed using a self-administered questionnaire designed based on an adapted eHealth readiness assessment model that covers six domains: core readiness, organizational cultural readiness, value proposition readiness, technological readiness, regulatory policy readiness, and operational resource readiness. The infrastructure and human resource capacity were assessed on-site using a tool adapted from the Technology Infrastructure Checklist. Internal consistency was assessed using Cronbach's alpha, and the significant relationship between the composite variables was assessed using Pearson's correlation coefficients (r).ResultWe assessed 14 facilities on-site and surveyed 60 TB and HIV healthcare providers. According to Cronbach's alpha test, all the six technology acceptance domains had a value of >0.8, suggesting a strong interrelatedness between the measuring items. The correlation between technological readiness and operational resource readiness was significant (r = 0.8). The providers perceived their work environment as good enough in electronic data protection, while more efforts are needed in planning, training, adapting, and implementing digital health. Of the 14 facilities, 64.3% lack the plan to establish a functional local area network, and 43% lack skilled staff on payroll to provide maintenance of computers and other digital technologies.ConclusionLike many developing countries, there was a modest infrastructure and human resource capacity and readiness of public healthcare facilities in Addis Ababa, Ethiopia, to nurture and strengthen DHIs across the TB and HIV cascades of care. Technological and operational resource readiness, including funding and a Well-trained workforce, are essential for successful implementation and use of digital health against the two infectious diseases of global importance in such settings.

New Lean Six Sigma readiness assessment model using fuzzy logic: Case study within clothing industry

The implementation of the Lean Six Sigma (LSS) in the textile and clothing industries is a successful strategy to reduce the defects produced along the production line in these industries. Lean Six Sigma readiness knowledge is a pre-requisite for a successful LSS implementation. Yet, the literature on Lean Six Sigma implementation and the readiness evaluation model in small and medium-sized textile and clothing are very limited. The purpose of this study is to develop a model of LSS readiness assessment for the clothing industries (LSRACI) using fuzzy logic. The present model is based largely on both the critical success factors (CSFs) of LSS and the LSS factors (enablers, criteria, and attributes) derived from the literature. The CSFs are identified using a questionnaire distributed to 85 small-medium clothing industries, and integration with the evaluation model. The outcome of this process is the identification of 5 enablers, 6 criteria, and 46 attributes which are finally ready to be used. The use of CSFs from the clothing industries gives a specification to our evaluation model and makes the LSRACI model original and specified to clothing SMEs. This model is developed for assessing the readiness level of the clothing and textile industries and it helps as well as to improve the readiness level for successful implementation of LSS. The present study aims to contribute to the knowledge of readiness for the LSS implementation in clothing industries. The readiness level of this company is average ready with (3.28; 4.9; 6.7). Using a fuzzy performance importance index (FPII), 20 from 46 attributes were identified as weaker attributes and therefore necessary corrective actions were recommended to improve the readiness level. The proposed model helps managers and practitioners to find out the potential of the clothing and textile industries by evaluating the company readiness before implementation in order to overcome problems and achieve a successful LSS implementation.

Creation of a Unified Cloud Readiness Assessment Model to Improve Digital Transformation Strategy

Digital transformation can disrupt any organization in any industry, but few organizations have successfully transformed. For an organization to transform digitally, a firm must adopt new technologies that enable it to change how it creates value. One of the most crucial new technologies organizations need to facilitate digital transformation is Cloud services. Cloud-based technologies are necessary for digital transformation because they allow a firm to cost-effectively obtain needed infrastructure capacity, processing, and developmental flexibility to support advanced analytical tools and methods. Implementing and adopting cloud services can be challenging and requires firm leaders and transformation teams to have an effective strategy that requires understanding a company's cloud readiness. Multiple organizational factors can impact cloud readiness, and depending on a firm's strengths or weaknesses, each element will support or hinder the adoption of cloud services. Understanding a firm's cloud readiness has been shown to improve an organization's adoption of cloud services, but assessing readiness can also be challenging since different assessment models determine readiness in varying ways. Readiness assessment models range from generic technology adoption models to specific cloud services readiness models, and a unified approach is needed that combines the strengths of each model to create a more comprehensive assessment model. A meta-analysis of current readiness assessment models was conducted to identify what crucial factors of an organization need to be assessed. The findings show that there seems to be significant agreement that a company's strategy, current technology, existing operations, and external factors are crucial readiness factors. More recent assessment models also identify gaps in past models, especially on human capital capabilities, system flexibility needs, and security. A more unified cloud assessment model is proposed based on the analysis showing that a firm's readiness should be based on seven crucial factors: strategy, technology, current operations, external requirements, human capital, system flexibility, and security. The new proposed assessment model provides a more comprehensive assessment of a firm's cloud readiness and enables organizations to create an improved adoptions strategy that will better support a company's digital transformation.

Supply Chain Management in Real Estate Practices: The Estate Surveyor and Valuers’ Perspective

Real estate practice is a strategic and multi-faceted vocation that connects the clients/owners of real estate projects or products with end users in the building industry. Different aspects of real estate practices require collaboration of real estate practitioners who are professional estate surveyors and valuers, with the built environment professionals and other stakeholders at different levels in order to achieve the transaction objectives. This study, therefore, examined the practice with a view to uncovering the preparedness of the estate surveyors and valuers with respect to the knowledge and application of supply chain management in real estate practices. Empirical data were collected with the aide of questionnaires administered to respondents from the 373 estate firms in Lagos State, Nigeria of which 291 were duly completed and returned constituting 78% rate of response. The Readiness Assessment Model was adapted to determine the operational preparedness of the estate surveying and valuation firms to implement supply chain management with regards to management readiness, employee readiness, services/processes readiness and logistic/ICT readiness on a 5-point Likert scale and the corresponding mean score and relative importance was determined. The Kolmogorov Smirnov Test of Normality was performed and showed that the data was normally distributed. Hence, the Pearson Product Moment Correlation analysis was used to determine the relationship between knowledge and application of supply chain management in real estate businesses. It was observed, among others, that the knowledge of supply chain management is generally low among estate valuers and does not necessarily translate to application in the property market transactions of real estate firms. The study further observed that management and employees of estate surveying and valuation firms do not have adequate knowledge of the principles and practices of supply chain management for productive engagement in property market transactions. This was further identified alongside others such as confidentiality, stiff rivalry and economic instability as critical factors resisting the adoption of supply chain management in the property market. The study therefore suggested capacity building programmes on supply chain management for the estate surveyors and valuers to improve the knowledge of the strategy and harness the benefits.

Conceptualizing Smart Manufacturing Readiness-Maturity Model for Small and Medium Enterprise (SME) in Malaysia

Manufacturing enterprises today are forced to face radical challenges in the disruptive concepts of Smart Manufacturing (SM) and Industry 4.0 to stay competitive. Most Multinational Enterprise (MNEs) have initiated their journey towards adopting SM. As a mainspring of many manufacturing economies, Small and Medium-Enterprise (SMEs) are still struggling to understand the complexity offered in SM, and many of them are not ready to embrace the concept of SM. To overcome this, SMEs first need to assess their readiness and maturity before embarking on an SM journey. The existing available readiness assessment model seems to be suitable for MNEs, and there is still a lack of tailored models that suit SMEs. This paper sought to pinpoint the conceptual framework from the review of the existing readiness-maturity assessment and identify the gap of existing model as well as proposed a tailored model framework that are suitable for SMEs. Ultimately, this model will be used to pursue a comprehensive scholarly study across Malaysia. The proposed model is enhanced with 4M attributes as the dimension and embedded with the characteristic of Industry 4.0 build component to help the SME’s overcome the possible uncertainties in adopting SM concept.

A holistic model for Global Industry 4.0 readiness assessment

PurposeTransformation to Industry 4.0 has become crucial for nations, and a coherent transformation strategy requires a comprehensive picture of current status and future vision. This study presents a comprehensive model for readiness assessment of nations based on rigorous analysis of several global indices and academic Industry 4.0 literature.Design/methodology/approachA holistic approach is taken considering overall socioeconomic development along with industrial innovation and seven readiness dimensions: enabling environment, human resource, infrastructure, ecological sustainability, innovation capability, cybersecurity and consumers. The indicators used for evaluation are standard metrics for which data are collected from reputed sources such as World Bank, United Nations Educational Scientific and Cultural Organization (UNESCO), World Economic Forum (WEF) and International Organization for Standardization (ISO), and hence internationally acceptable.FindingsThe formulated model is used to evaluate Industry 4.0 readiness of 126 economies that account for 98.25% of world’s gross national income. Observations show poor scores of most economies on innovation capability and cybersecurity dimension as compared to other 5 dimensions. In 75% countries, I4.0 readiness score is below 0.5 on a scale of 0–1(completely ready), highest being 0.65 for Denmark.Originality/valueA systematic literature review revealed lack of assessment models discussing a nation's current status or readiness for Industry 4.0. This academic study is first of its kind.

The Application of TRIZ in The Development of Readiness Assessment Model for The Malaysian Industry4WRD Program

The global industrial revolution has become a major concern for most organizations in the effort to innovate and improve towards competitiveness and sustainability. This initiative has been considered as a disruptive change in manufacturing and also services. Many countries have taken proactive action to learn and adopt the concept of Industry 4.0 in order to be at the front edge of transformation. However, various countries and government agencies are trying to support the local industries with limited knowledge and resources, especially in developing countries such as Malaysia. This paper focuses on the challenges in developing the Industry 4.0 readiness assessment model by adopting innovative methodology called TRIZ. This model is useful in helping the Malaysian government agencies to guide and facilitate the transformation program of Industry 4.0 that has been given a new brand name which is Industry4WRD. The Malaysian industries are able to identify the gaps within the organization and the benchmark with the best practiced Industry 4.0 company by using the readiness assessment tools that have been developed from the research. TRIZ has been the core concept of the readiness assessment model and has also effectively shown result from a case study that is presented in this paper