Lean management has generated new approaches to reduce non-value-adding activities in different sectors of the economy, including in higher education systems. Lean principles in higher education institutions (HEIs) contribute positively to sustainability performance. The current study aims to: (a) assess waste in HEIs based on lean principles and even their potential effect on sustainability; (b) establish the relationship among wastes; (c) develop a structural model using Interpretative Structural Modeling (ISM); (d) carry out the Matrice d’impacts Croisés Multiplication Appliqué Àun Classement (MICMAC) analysis. In Phase 1 of this study, the identification of waste modes in HEIs was established. In Phase 2, risk assessment of each waste mode was conducted using the waste-Failure Mode and Effect Analysis (w-FMEA) technique. In Phase 3, ISM-MICMAC was used to identify relationships among critical waste modes. The results showed that eighteen waste modes were identified as critical in HEIs—with six waste modes being autonomous determinants; four were dependent determinants, four were linkage determinants, and four were driver determinants. This study is expected to help academicians and practitioners understand HEI’s waste types by listing the critical wastes, mapping their interrelationship, identifying the driving power and dependence, and proposing mitigation actions. It will also contribute to the growing body of literature highlighting the waste in HEIs.

Waste in HEIs is difficult to identify, so identifying and prioritizing waste is challenging. This research aims to develop a framework within which to identify and prioritize waste reduction in HEIs. The novelty of this study is that it analyzes and prioritizes waste in HEI from the perspective of four stakeholders in teaching, research, and community services, as well as supporting activities. The process of waste identification was undertaken via observation and literature review, while prioritization of waste was based on the criticality level of waste (CLoW). Determining the criticality level of waste (CLoW) consists of two stages: the first stage is calculating waste scores using questionnaires from students, lecturers, and education staff; the second stage is calculating the critical level of waste using a questionnaire from HEI leaders and analyzing it with fuzzy methods. This study identified 59 types of waste and grouped them into eight types: over-production, over-processing, waiting, motion, transportation, inventory, defects, and underutilization talent. Waste occurs in three HEI activities: teaching, research, community service, and supporting activities. The results also show the priority order of waste reduction and proposed improvements to reduce waste. This study offers a practical contribution to the management of HEIs to identify and prioritize waste reduction. The theoretical contribution of this study is that it fills the research gap of waste reduction prioritization in all aspects of HEI activities involving all HEI stakeholders involved in the business process, namely, students, academics, non-academic staff, and HEI leaders.

Lean is a philosophy that is seen as a solution to resolve the problem of efficiency in various industries. It can be used to eliminate all forms of waste in the workplace. The implementation of lean is not only applied in manufacturing but is very important to be applied in other fields, such as in Higher Education Institution. Studies on the topic of lean in the workplace have been carried out, but most of the study has been conducted within a manufacturing context. This study aims to determine the type of waste that is most important to be eliminated first by using the Waste Assessment Model and find the root of the waste problem. This study developed the relationship between waste and find out the effect of waste on each other in Higher Education Institution that focused on teaching and learning process. The steps of this study consist of three-step, such as waste identification, waste assessment, and root cause analysis. From data collection show that there are 46 forms of waste in the teaching and learning process. The results of the Waste Relationship Matrix showed three types of waste must be removed first, namely overproduction, defects, and non-utilized talents. 5-Why’s is used to find out the root causes of waste which is the most important to be eliminated first in the teaching and learning process.

To improve a traceability system, both the internal and the chain one, the first important step is to identify the Critical Traceability Points (CTPs) along the supply chain. Therefore, the purpose of this study is to map out the CTPs of the Indonesian coconut oil company as the basis for improving the traceability system. Process mapping was used as the method to capture the CTPs in the production of Refined Bleached Deodorized Coconut Oil (RBDCNO). Critical Traceability Point Analysis (CTPA) was performed to find the feasible traceability improvement strategies. The process mapping successfully identified 13 CTPs from the reception of raw materials to the dispatch of finished products. The recommended improvement strategies are to integrate the identification record of material flow along the process and to develop an internal code system that allows the company to trace and track. This recommendation can be implemented by converting the information system into a digital system.

Lean Six Sigma (LSS) is a strategy to overcome the problems that occur to improve the efficiency and effectiveness of the company through the elimination of variation and waste. efficiency and effectiveness will ensure the sustainability of the company. Several factors affect the success of LSS implementation in the company. Therefore, to be successful in LSS implementation, an assessment is needed to measure the level of LSS readiness (Lean Six Sigma Readiness/LESIRE). This article discusses the measurement of the readiness level of the plastic industry in Indonesia in the implementation of LSS. In addition to measuring the level of readiness, this article also discusses what important factors must be prepared in advance to be ready for LSS implementation. Data was collected by distributing questionnaires and processed using the fuzzy method. Factors that influence success consist of 5 enablers, 19 criteria, and 55 attributes. The results showed that the industry studied was categorized as Almost Ready. Attributes that need to be improved to increase LSS readiness are company initiatives in development, learning processes in development, improving workforce skills, customer-focused organizations or companies, strategic and visionary leadership, responsibility, authority and communication, planning, feedback loop design, eliminating waste, high impact of customer satisfaction, and technology improvement.

Perkembangan teknologi menuntut segala sesuatu dilakukan serba cepat, praktis, dan efektif efisien. Hadirnya dompet digital menggunakan sistem elektronik berbasis internet, sistem kerja dapat meringkas segala transaksi keuangan dibandingkan dengan transaksi konvensional. Penelitian ini menganalisis faktor-faktor yang mempengaruhi pemilihan penggunaan dompet digital di Kota Surabaya, dengan melakukan analisis cluster pada profil responden yang didapat dan analisis diskriminan untuk menemukan perbedaan tiap cluster. Dilakukan analisis faktor dari variabel-variabel yang telah ditentukan sehingga didapatkan hasil kemudahan, kemampuan finansial, kecepatan bertransaksi, keamanan, promosi, dan pengaruh sosial berpengaruh terhadap pemilihan penggunaan dompet digital. Terbentuk 2 cluster responden, sedangkan yang menjadi pembeda adalah tingkat penghasilan oleh konsumen.