Synchro-Modality and Slow Steaming: New Business Perspectives in Freight Transportation

Perboli, Guido; Musso, Stefano; Rosano, Mariangela; Tadei, Roberto; Moritz, Godel

doi:10.3390/su9101843

Cited by 43 publications

(28 citation statements)

References 11 publications

(17 reference statements)

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“…Second, the incubators/accelerators should think to a post-incubation phase where a company/group specialized in Business Development is put aside the startup. A partial answer to the first point is emerging from some developments of the Lean Startup philosophy, as the GUEST Business method [61][62][63].…”

Section: Final Remarksmentioning

confidence: 99%

Startups’ Roads to Failure

et al. 2018

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The role of a relatively small cadre of high-tech startup firms in driving innovation and economic growth has been well known and amply celebrated in recent history. At the same time, it is well recognized that, while the overall contribution of startups is crucial, the high-risk and high-reward strategy followed by these startups leads to significant failure rates and a low ratio of successful startups. So, it is curious to notice that literature tends to focus on successful startups and on quantitative studies looking for determinants of success while neglecting the numerous lessons that can be drawn by examining the stories of startups that failed. This paper aims to fill this gap and to contribute to the literature by providing a repeatable and scalable methodology that can be applied to databases of unstructured post-mortem documents deriving startup failure patterns. A further and related contribution is the analysis carried out with this methodology to a large database of 214 startup post-mortem reports. Descriptive statistics show how the lack of a structured Business Development strategy emerges as a key determinant of startup failure in the majority of cases.based on discriminant analysis [5] and multiple discriminant analysis [4], followed by more recent approaches exploiting regression [6][7][8]. Since the 80s, artificial intelligence methods started to be used as well to predict ventures success/failure. Suggested solutions relied on decision trees algorithms [9], artificial neural networks [10], clustering [11] and hybrid genetic algorithms [12]. Approaches based on financial data had the advantage of being potentially applied to a high number of companies, since data could be gathered from their annual reports. Nonetheless, company revenues were frequently consequences of other aspects, such as entrepreneur's ability, company's core competencies, market, etc. In this view, other research works investigated whether such aspects could contribute as well to the success or failure of a venture. For instance, analysis conducted on entrepreneurs examined the influence of their gender and ethnic origin on the likelihood to succeed or fail [13,14]. The work in [15] conducted a logistic regression analysis based on 15 independent variables success versus failure prediction model in Israel, including the management experience, the education, and the age of the owner. The logistic regression analysis was also adopted in [16] to model the relationship between small business mortality rates and the aggregate levels of internal and external risks (e.g., bankruptcy related to interest rates, discontinuance of business or of ownership, etc.). Other researchers focused on entrepreneurial attitudes and linked startup failure to dissonances between corporate goals and the goals of its founders [17]. Others presented failure as the result of entrepreneurs' overconfidence and hubris [18]. In contrast, other researchers argued that, without a reasonable level of positive perception of one's abilities, several successful...

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Section: Final Remarksmentioning

confidence: 99%

Startups’ Roads to Failure

et al. 2018

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“…In slow/smart steaming, the cargo ships are operated at significantly lower speeds than their design speeds to achieve fuel cost reduction and lower greenhouse gas emissions. Synchro modal transport also considers the stakeholders' requirements to provide a strategy that can incorporate slow steaming to reduce the environmental burden (Perboli 2017) [22].…”

Section: Performance and Sustainability Of Dry Portsmentioning

confidence: 99%

Engaging Employees with Good Sustainability: Key Performance Indicators for Dry Ports

2019

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Dry ports have the potential to enhance the sustainability of transport systems, yet their introduction requires major changes to the current logistics chain. Further, emphasising sustainability goals and continued employee engagement can be a challenge when developing or implementing organisational change management programs in dry ports. Key considerations include governmental requirements and compliance, investor expectations, as well as employee engagement; these factors may be conflicting. The top-down management approach supported by strong leadership, participative approaches and constant communication assists in achieving successful change management. Sound selection of key performance indicators (KPIs) provides a set of metrics to track and aid the change process. They serve as a unifying link between top managements’ sustainability goals and employees’ engagement. The initial findings of our research confirm that both port and terminal operators have a gap in their understanding of the importance of sustainability goals and environmental goals. This will have a flow-on effect of port and terminal operators not driving the right messages to their staff in their organisational change management programs. Based on a critical literature review, it has been established what might qualify as good sustainability KPIs for dry ports. An example of a dry port at the Port of Somerton has been included. As every dry port has different requirements and constraints, it is important to develop KPIs together with stakeholders.

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“…Brown and Guiffrida [34] highlight that the particular capacity in private vehicles is not used to its full capacity. Furthermore, just-in-time delivery, with its small loads in rapid time, is responsible for unutilised capacity [9,39,43]. Vehicle loading, empty running, vehicle time utilisation, and deviation from schedule, are proposed by McKinnon and Ge [38] as key performance indicators (KPIs) in order to evaluate capacity utilisation.…”

Section: Systems Perspective On Capacitymentioning

confidence: 99%

Energy Efficiency in Logistics: An Interactive Approach to Capacity Utilisation

Wehner

2018

Sustainability

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Logistics operations are energy-consuming and impact the environment negatively. Improving energy efficiency in logistics is crucial for environmental sustainability and can be achieved by increasing the utilisation of capacity. This paper takes an interactive approach to capacity utilisation, to contribute to sustainable freight transport and logistics, by identifying its causes and mitigations. From literature, a conceptual framework was developed to highlight different system levels in the logistics system, in which the energy efficiency improvement potential can be found and that are summarised in the categories activities, actors, and areas. Through semi-structured interviews with representatives of nine companies, empirical data was collected to validate the framework of the causes of the unutilised capacity and proposed mitigations. The results suggest that activities, such as inflexibilities and limited information sharing as well as actors' over-delivery of logistics services, incorrect price setting, and sales campaigns can cause unutilised capacity, and that problem areas include i.a. poor integration of reversed logistics and the last mile. The paper contributes by categorising causes of unutilised capacity and linking them to mitigations in a framework, providing a critical view towards fill rates, highlighting the need for a standardised approach to measure environmental impact that enables comparison between companies and underlining that costs are not an appropriate indicator for measuring environmental impact.

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Synchro-Modality and Slow Steaming: New Business Perspectives in Freight Transportation

Cited by 43 publications

References 11 publications

Startups’ Roads to Failure

Startups’ Roads to Failure

Engaging Employees with Good Sustainability: Key Performance Indicators for Dry Ports

Energy Efficiency in Logistics: An Interactive Approach to Capacity Utilisation

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