Why Are Electronic Invoice Processes Risky? - Empirical Analysis and Discussion of Risk Factors

Electronic invoice processes are characterized by various software solutions, legal uncertainty, heter-ogeneous demands, lack of know how, and information system infrastructure incompatibilities. Due to this complexity and the uncertainty that companies face, a holistic map of risk factors of e-invoice processes is required. Companies must be conscious not only about potential opportunities but also about potential risks before they change their business processes and their information systems’ archi-tecture. Potential risk factors are identified theoretically and empirically evaluated with a quantitative expert survey that investigates risk probabilities and potential losses associated with these factors. The empirical analysis reveals that the investigated factors are valid and reliable. After conducting an ex-plorative factor analysis, 37 statistically significant risk factors are grouped into ten risk dimensions: process organization, standard, environment, project management, strategy, acceptance, system, pro-cess execution, security, and change management

Contributions to the selection and implementation of standard software for CRM and electronic invoicing

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Artificial Intelligence in Supply Chain and Operations Management: A Multiple Case Study Research

Artificial intelligence (AI) is increasingly considered a source of competitive advantage in operations and supply chain management (OSCM). However, many organisations still struggle to adopt it successfully and empirical studies providing clear indications are scarce in the literature. This research aims to shed light on how AI applications can support OSCM processes and to identify benefits and barriers to their implementation. To this end, it conducts a multiple case study with semi-structured interviews in six companies, totalling 17 implementation cases. The Supply Chain Operations Reference (SCOR) model guided the entire study and the analysis of the results by targeting specific processes. The results highlighted how AI methods in OSCM can increase the companies' competitiveness by reducing costs and lead times and improving service levels, quality, safety, and sustainability. However, they also identify barriers in the implementation of AI, such as ensuring data quality, lack of specific skills, need for high investments, lack of clarity on economic benefits and lack of experience in cost analysis for AI projects. Although the nature of the study is not suitable for wide generalisation, it offers clear guidance for practitioners facing AI dilemmas in specific SCOR processes and provides the basis for further future research

A Decision Tool for Supplier Selection That Takes into Account Power and Performance

Companies select their suppliers to provide required performance while being successful partners. An important aspect of collaboration is the power relationship between the company and its suppliers. Although the significance of power in supplier selection is acknowledged, published work rarely includes assessment of power. An empirical study on selecting suppliers for new product developments in a major European diesel engine manufacturing company, supported by three smaller studies with electronic engineering companies, frames overall questions regarding the importance of incorporating power into supplier selection and how this might be achieved. This research proposes an approach that assesses both performance and power and integrates the assessment results by modelling the relative effects of power and performance. It positions the suppliers into six scenarios (ideal, satisfying, tolerable, unfavourable, risky and tough) which depict to what extent a supplier is ‘suitable’ to work with. A reverse analysis reviews the relationship when several suppliers appear suitable. An assessment method is developed incorporating both subjective and objective data for qualitative and quantitative criteria. It combines two decision making methods, AHP and TOPSIS, with triangular fuzzy numbers. Multiple judgements from several decision makers are synthesised. This method is adapted for performance assessment of single, group and cross-group suppliers. Weights are calculated for the criteria, and combined with calculations of supplier performance against each criterion to provide an overall assessment and supplier profile. Power is quantified against a set of power determinants and power relations (supplier dominance, buyer dominance and balanced) are determined. The effects of supplier perceptions (objective, optimistic and pessimistic) are estimated in the calculation. The proposed approach involves complex calculations and a prototype software tool is developed with graphical interfaces. The tool includes performance criteria and power determinants collected from literature and allows users to define new ones. Application to an agriculture case enables the sustainable performance of suppliers (farmers) to be evaluated and compared

Managing Opperational Supplier Relationships

Background: The Company is in process of increasing the level of centralisation to make use of the economy of scale and get a stronger buying position. A common supplier relationship process on operational level is part of this process. Purpose: Purpose of the thesis is to review and improve the operational supplier relationship management process at The Company. The aim is to define and analyse the process and identify activities in need of improvement in order to achieve a structured and standardised supplier relationship management process for major appliances in Europe. Objectives: In order to fulfill the purpose of this thesis the following objectives need to be met: • Identify, define and map the current state of the operational supplier relationship process at The Company. • Define a structured model, based on the product characteristics, to achieve standardised operational activities in the supplier relationship. • Present recommendations aiming to improve the supplier relationship management process by changes in operational activities. Method: This thesis has been conducted using a systems approach. By combining theories from supply chain management and supplier relationship management with empirical studies from The Company operations a operational supplier relationship process was elaborated and validated with experienced personnel. Result: The thesis resulted in a supplier segmentation model and a process for operational work with Supplier Relationship Management

Proactive model to determine information technologies supporting expansion of air cargo network

Shippers and recipients expect transportation companies to provide more than just the movement of a package between points; certain information must be available to them as well, to enable forecasts and plans within the supply chain. The transportation companies also need the information flow that undergirds a transportation grid, to support ad-hoc routing and strategic structural re-alignment of business processes. This research delineates the information needs for an expanding air cargo network, then develops a new model of the information technologies needed to support expansion into a new country. The captured information will be used by shippers, recipients, and the transportation provider to better guide business decisions. This model will provide a method for transportation companies to balance the tradeoffs between the operating efficiencies, capital expenditures, and customer expectations of their IT systems. The output of the model is a list of technologies – optimized by cost – which meet the specific needs of internal and external customers when expanding air cargo networks into a new country

Supply Chain Risk Management Study of the Indonesian Seaweed Industry

Die Supply Chain von Algen in Indonesien, insbesondere Karrageen und Agarprodukte, ist mit Störungen innerhalb der Unternehmen und in externen Netzwerken konfrontiert wie z. B. Quantität, Qualität, Preis und Infrastruktur. Sobald eine Störung in einem Teil der Supply Chain auftritt, kann diese die gesamte Wertschöpfungskette beeinflussen. Um eine nachhaltige Algenindustrie sicher zu stellen, bedarf es einer langzeitigen Planung. Hierbei kann das Supply Chain Risk Management (SCRM) helfen. SCRM umfasst vier kritische Stufen: Identifikation der Algen-Supply Chains, Identifikation und Kategorisierung der Risiken, Einschätzen der Risiken und Vermeidung der Risiken. Um die Algen-Supply Chains zu identifizieren, wurden Feldforschung, Tiefeninterviews und Literaturrecherchen durchgeführt. Die Feldstudie wurde in den Provinzen Süd-Sulawesi, West-Java, Ost-Java, Banten und West-Nusa Tenggara durchgeführt. Anschließend wurden die Algen-Supply Chains mit der Software Umberto NXT Universal 7.0 modelliert, um ein besseres Verständnis von den Material- und Energieflüssen zwischen den Hauptakteuren zu erhalten. Um die Risiken zu identifizieren und zu kategorisieren wurden Literaturrecherchen durchgeführt und die Delphi Methode angewandt, um potentielle Quellen der Risiken, ihre Gründe und ihre Effekte zu analysieren. Zur Einschätzung der Risiken wurde ein semi-quantitativer Ansatz gewählt, welcher auf Face-to-face Interviews zurückgreift. Dementsprechend wurde eine Risikokarte erstellt, welche die Wahrscheinlichkeiten und Effekte von ungünstigen Ereignissen widerspiegelt. Basierend auf den vorherigen Ergebnissen wurde die Intensität der Risiken in die folgenden fünf Kategorien unterteilt: vernachlässigbare, geringe, kritische, sehr kritische und katastrophale Risiken. Drei alternative Strategien zur Vermeidung der Risiken werden vorgeschlagen: der Bau einer kleinen Algen-Fabrik, große Algen-Herstellung und industrielle Algen-Cluster, welche direkt am Algenanbau angegliedert sein müssen. Um die Strategien zu bewerten wurde die Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) angewandt, welche der multikriteriellen Entscheidungsanalyse zuzurechnen ist. Die Vermeidungsstrategien berücksichtigen  Nachhaltigkeitskriterien (Ökologie, Wirtschaft, Soziales) und Risikokriterien. Die Ergebnisse zeigen, dass Algen-Supply Chains mit vertikaler Kooperation, aus Algen-Lieferanten (Farmer, lokale Händler, Großhändler und Exporteure) und Algen-Herstellern (Carrageen- und Agarunternehmen) bestehen. Die meisten Algen-Farmer sind unabhängige Farmer, die die Möglichkeit haben die Algen entweder an lokale Händler oder andere je nach Präferenz verkaufen können. Lokale Händler spielen eine entscheidende Rolle hinsichtlich der finanziellen Unterstützung der Farmer, der technischen Informationen und des Marktzugangs. Indonesische Carrageen- und Agarhersteller weisen ein kontinuierliches Marktwachstum auf, insbesondere als Familienunternehmen. Die Risiken der Algen-Supply Chain werden in zwei Hauptkategorien unterteilt: interne und externe Risiken. Interne Risiken werden weiterhin in zwei Gruppen untergliedert: interne Unternehmensrisiken, welche aus Prozess- und Steuerungsrisiken bestehen, sowie externe Unternehmensrisiken, die Supply- und Nachfragerisiken umfassen. Externe Supply Chain Risiken, die aus externen Netzwerkketten resultieren, sind Risiken hinsichtlich regulatorischer Fragen, der Finanzierung, Infrastruktur als auch soziale und umweltbezogene Risiken. Als kritischstes Risiko für die Carrageen-Supply Chain wurde die mangelnde Qualität von E.cottonii rohgetrockneten Algen identifiziert. Weitere kritische Risiken der Agar-Supply Chain sind Quantitätsunsicherheiten, die Knappheit von Gracilaria roh getrockneten Algen sowie negative Umweltauswirkungen des Abwassers. Aus  der Fallstudie zu halb-raffinierten Karrageen resultierte das Clustern von Algen-Verarbeitungsbetrieben als ist die beste Risikovermeidungsstrategie sowohl für große als auch kleine Unternehmen. Nichtsdestotrotz kann sich das Clustern negativ auf die lokale Umwelt auswirken.